Jul 25, 2016 - A track day racing car has a lot of subsystems which requires individual ..... Most of the EV's are manufactured to use in domestic life. ... After inventing the lead acid batteries and the electric motors in late 1800s, the first.
Battery Cell Monitoring and Balancing System for a Track Day Electric Car
A. S. Palihawadana Student No: 1331276
Under the Supervision of Dr. S. D. R. Perera & Eng. W. R. D. R. Perera
A thesis submitted in partial fulfilment of the Requirements of University of Wolverhampton for the Degree of Bachelor of Engineering In Mechatronic July 2016
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Student’s Declaration I hereby declare that the work in this project is my own except for quotations and summaries which have been duly acknowledged. The project has not been accepted for any degree and is not concurrently submitted for award of other degree.
…………………………. Signature
Name:
A. S. Palihawadana
Student ID Number: 1331276 Date:
25 JULY 2016
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Abstract Global warming and environmental pollution is a major threat to the mankind and to the earth in the 21st century. There are many reasons for the global warming. Higher percentage of the pollution happens because of the transportation. Earliest days travelling was done by using animals like horse’s, by cows etc. Later on people began to improve the transportation because it helped to do their day-to-day activities easily. Huge revolution took place when the combustion engine was invented in 1798 by John Stevens. Time past and today it has come to a huge successes. Fossil fuel is the main source of the combustion engine. Hence the fuel is a diminishing resource, the prices of which continue to rise. So alternative energy should be used to overcome this issue. Electricity is a one solution for that. Then the hybrid and full electric vehicles came to the market. Racing is a popular sport from the beginning of the motor vehicle age. When the fossil fuel is over will that sport stop. Then the experts have convert racing cars to electric. Then the electric racing has begun. This report consists of the battery management system of a track day Formula one type electric racing car. Electrical energy is a good source of energy for electric cars. However the capacity of electrical energy is limited and also there are lots of resistive forces. So then the electrical energy should be handled more efficiently. The main goal of this research is managed the regenerative breaking energy more efficiently and also improve usability of the battery bank itself by reducing the resistive forces like resistance and temperature of circuits. Super capacitor based regenerative energy storage system is going to be used. Li-ion battery cells are going to be used as the main storage source and an auxiliary battery will be installed to power up the system circuits and the other electric equipment’s in the car.
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Acknowledgement With a grateful heart, I would like to acknowledge all members of staff at the Engineering Department of CINEC for their immense contributions in my academic endeavours. Thank you for everything you have done to me, day after day, year after year. Special thanks goes to Head of department of the Engineering department Mr. T. S. Peris who played a major role withstanding with us to bring this project to success. I would like to specially thank CINEC campus who gave us financial support to succeed our project. I would also like to thank University of Wolverhamton to providing vital rage of learning resources and learning materials on their resource page. It helped me to find literature about my project without difficulty. I wish to express profound gratitude to my supervisors, Dr. S. D. R. Perera and Eng. W. R. D. R. Perera for providing very vital assistance and guidance to design the Battery Management System successfully. I appreciate his timely review and thoughtful assessment of the project progress. Also I like to thank my team e-wolf members who supported me, encouraged me and guided me to complete my project when difficulties came. My special thanks goes to our team leader Dasith who gave full effort to succeed our tasks. Also I would like to mention my other batch mates who supported me to do this project successfully. To the Supreme Creator and Sustainer of the universe, your intelligent design concepts fill me with wonder. I appreciate and value your grace, goodness and bountiful blessings in my life.
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Scope of Research A track day racing car has a lot of subsystems which requires individual attention. Each subsystem has a countless opportunity on the vehicle. Every system is equally important. This study is about the battery management system of the track day electric car. Improve the distance can be travelled under a single charge and improve system performance is the main purpose of this project. The plug in charging circuit for the battery pack is not part of this project. Cell balancing and the cell monitoring systems are going to be designed and implemented. A voltage sensing system also made for the SOC estimation process. A temperature measuring system with fan is going to design and implement and the fane speed will adjust for different temperature values. In high temperature the fan will operate in high speed to cool rapidly and in low temperature the fan will drop its speed to reduce the power usage. Each cell voltage, available battery charge and the charging or discharging current will be displayed by using a LCD display. A power supply circuit for the system circuits going to be implemented. The high voltage and system protection circuits are going to be developed in future. For the implementation three cell, sample battery monitoring and cell balancing pack will be made. Three 3.6V and 2,250 mAh capacity batteries are using to develop the sample system. The data sheet is attached in appendix 03. Additional power storage is going to be placed to supply power to the adaptive spoiler, the instrument cluster and the operating circuits. Increasing the temperature around the battery system has an impact on the current flow and the state of charge of the batteries. So to keeping a constant temperature range around the battery and the motor is going to be analyzed by this research. Li-ion batteries will be used for the BMS. Battery capacity of Li-ion battery is higher than the other batteries available in the market. However when considering the price Li-ion batteries are more expensive than other battery types.
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Contents 1.0
Introduction………………………………………………………………. 1
2.0
Literature Review………………………………………………………… 6 2.1
Electric Vehicle Operation………………………………………… 7
2.2
Available Battery Varieties for EV’s……………………………… 9 2.2.1
Lead-acid battery………………………………………….. 11
2.2.2
Lithium-ion Battery……………………………………….. 15
2.2.3
Nickel Metal Hydride Battery…………………………….. 19
2.2.4
Lithium Polymer Battery………………………………….. 20
2.2.5
Fuel Cell Technology……………………………………… 21
2.3
Future Batteries……………………………………………………. 23
2.4
Modelling of a Battery…………………………………………….. 25
2.5
Battery Management System Architectures………………………. 28
2.6
Battery Cell Balancing Methods………………………………….. 33 2.6.1
Passive Balancing Methods……………………………….. 37
2.6.2
Active Balancing Methods………………………………… 38 2.6.2.1 Capacitive Shunting Cell Balancing………………. 38 2.6.2.2 Inductor/Transformer cell Balancing……………… 40 2.6.2.2.1 Single or Multi-inductor………………… 40 2.6.2.2.2 Single-Winding Transformer…………… 41 2.6.2.2.3 Multi-Winding Transformer……………. 41 2.6.2.3 Energy Converter Based Cell Balancing…………. 44 2.6.2.3.1 Cuk Converter…………………………... 44 2.6.2.3.2 Buck, Boost or Buck/boost Converter…... 44 2.6.2.3.3 Flyback Converter………………………. 45 2.6.2.3.4 Ramp Converter………………………… 46 2.6.2.3.5 Full-Bridge Converter…………………... 46 2.6.2.3.6 Quasi-Resonant Converter………………. 47
2.7
Battery Cell Balancing System Control……..……………………. 47 2.7.1
Available Controlling Switch Types……………………… 47 2.7.1.1 Solid-State Relay…………………………………. 48 2.7.1.2 MOSFET………………………………………….. 50
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State of Charge (SOC) Estimation……………………….... 53 2.7.2.1 OCV State of Charge Estimation………………….. 56
2.7.3 2.8
3.0
State of Health Estimation (SOH)…………………………. 57
Li-ion Battery Charging, Discharging and System Safety………... 59 2.8.1
CVL & DVL of a Battery…………………………………. 59
2.8.2
Battery Discharging Process………………………………. 60
2.8.3
Battery Charging Process…………………………………. 62
2.8.4
High Voltage System Safety…………………………….... 65
Project Analysis………………………………………………………….. 68 3.1
Electric Vehicle Battery Type Selection………………………….. 69
3.2
Battery Management System Architecture Selection…………….. 71
3.3
Cell Balancing Method Selection………………………………… 74
3.4
Analysis of State of Charge Estimation………………………….. 77
3.5
Balancing Control with Open Circuit Voltage SOC Estimation…. 80 3.5.1 Designing Limitations of OCV Based SOC Estimation……. 80 3.5.2 Cell Balancing Technique…………………………………... 82
4.0
System Design……………………………………………………………. 89 4.1
Li-ion Battery Selection…………………………………………... 90
4.2
Battery Management Architecture design………………………… 94
4.3
Cell Voltage Measuring System Design………………………….. 98
4.4
Current Sensing System Design………………………………….. 103
4.5
Temperature Sensing and Battery Cooling System Design………. 107
4.6
Cell Balancing System Design…………………………………… 115 4.6.1 Selection of MOSFETs…………………………………….. 116 4.6.2 Isolation of the MOSFET Controlling Signal……………… 120 4.6.3 Design of Signal Amplifier for the Optocoupler IC………... 125 4.6.4 Selection of Capacitors in the Balancing Circuit…………… 128 4.6.5 Switching Algorithm of the Cell Balancing Circuit………... 130
4.7
System Interface LCD Design……………………………………. 138
4.8
System Power Supply…………………………………………….. 140
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System Implementation and Testing…………………………………... 141 5.1
PCB Designs of the System Circuits…………………………….. 142 5.1.1 Designing of the Voltage Sensing Circuit PCB……………. 142 5.1.2 Cell Balancing Circuit PCB Design………………………..
145
6.0
Conclusion………………………………………………………………. 147
7.0
References……………………………………………………………….
150
Appendix Appendix 01 – NCR18650A Li-ion battery datasheet…………………………..
II
Appendix 02 – UR18650ZTA Li-ion battery datasheet…………………………
III
Appendix 03 – CGR8650CG Li-ion battery datasheet………………………….
IV
Appendix 04 – Valence IRF26650PC Li-ion battery datasheet…………………
V
Appendix 05 – A123 System ANR26650m1-B datasheet………………………
VI
Appendix 06 – Texas instrument BQ76PL536 datasheet……………………….
VIII
Appendix 07 – Linear technologies LTC6802-1 datasheet……………………...
XIII
Appendix 08 – 20kW BLDC motor performance curve datasheet……………....
XVI
Appendix 09 – OPA277 operational amplifier datasheet………………………..
XVII
Appendix 10 – ACS 712 current IC datasheet…………………………………..
XXI
Appendix 11 – LM35 temperature sensor datasheet…………………………….
XXIV
Appendix 12 – L293D motor driver IC datasheet……………………………….
XXIX
Appendix 13 – FQP30N06L N-channel MOSFET datasheet…………………...
XXXII
Appendix 14 – STP30NF10 N-channel MOSFET datasheet……………………
XXXV
Appendix 15 – BUZ71A N-channel MOSFET datasheet………………………. XXXVIII Appendix 16 – 6N136 optocoupler IC datasheet………………………………..
XLI
Appendix 17 – TL081 op-amp datasheet………………………………………..
XLIV
Appendix 18 – LM7805 voltage regulator………………………………………
XLVII
Appendix 19 – LM3224 voltage step-up IC datasheet………………………….
XLVIII
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List of Figures Chapter 01 Figure 01 – Crude oil imports (unit price movements)…………………………..
2
Figure 02 – A track day car…………………………………................................
5
Figure 03 – Benz SLS electric car……………………………………………….. 5
Chapter 02 Figure 04 – Global EV sales……………………………………………………... 8 Figure 05 – The traditional Pb-acid battery……………………………………… 12 Figure 06 – Battery molality vs battery cell voltage Pb-acid…………………….
14
Figure 07 – Power vs temperature Pb-acid………………………………………
15
Figure 08 – Li-ion battery varieties……………………………………………...
16
Figure 09 – Safe operating area charging and discharging Li-ion………………
17
Figure 10 – Charging and Discharging of Li-ion batteries………………………
18
Figure 11 – Basic fuel cell battery……………………………………………….
22
Figure 12 – Future and present Li-ion battery cells……………………………...
23
Figure 13 – Cell resistance, cell capacity varying with the time………………...
25
Figure 14 – Various models of battery…………………………………………..
26
Figure 15 – Equivalent model for a single cell…………………………………..
27
Figure 16 – Battery management subsystems……………………………………
29
Figure 17 – Battery management system signal flow chart……………………...
30
Figure 18 – Battery management system architectures………………………….
31
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Figure 19 – Battery cell balancing topologies…………………………………...
35
Figure 20 – Cell balancing comparison………………………………………….
36
Figure 21 – Fixed resister cell balancing………………………………………...
37
Figure 22 – Control shunting resister cell balancing…………………………….
37
Figure 23 – Modularized switched capacitor balancing…………………………
38
Figure 24 – Switched capacitor cell balancing…………………………………..
38
Figure 25 – Single switched capacitor cell balancing …………………………...
39
Figure 26 – Double-tiered switched capacitor cell balancing …………………...
39
Figure 27 – Single inductor cell balancing……………………………………....
40
Figure 28 – Multi inductor cell balancing……………………………………….
40
Figure 29 – Pack-to-cell single-winding transformer cell balancing……………
41
Figure 30 – Flyback cell balancing……………………………………………...
42
Figure 31 – Forward cell balancing……………………………………………..
42
Figure 32 – Multiple transformer cell balancing………………………………..
43
Figure 33 – Multi inductor cell balancing……………………………………….
44
Figure 34 – DC/DC converter cell balancing…………………………………....
45
Figure 35 – Bidirectional flyback converter cell balancing……………………..
45
Figure 36 – Ramp converter cell balancing……………………………………..
46
Figure 37 – Full-bridge cell balancing…………………………………………..
46
Figure 38 – Solid-state relay concept…………………………………………....
48
Figure 39 – A solid state relay…………………………………………………...
49
Figure 40 – Solid-state relay inside mechanism…………………………………
50
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Figure 41 – MOSFET construction………………………………………………
51
Figure 42 – Gate oxide layer……………………………………………………..
51
Figure 43 – N & P channel MOSFET symbols………………………………….. 51 Figure 44 – A MOSFET…………………………………………………………. 52 Figure 45 – Closed loop kalman filtering battery model………………………… 55 Figure 46 – Battery cell voltage and SOC variation during charging & discharging…………………..
56
Figure 47 – CVL and DVL range of a battery…………………………………...
59
Figure 48 – Battery voltage diagram to different discharging capacities………..
61
Figure 49 – Charging characteristics of Panasonic NCR18650A Li-ion………...
62
Figure 50 – Smart charging process of electric vehicle………………………….. 63 Figure 51 – Time controlling charging pattern…………………………………... 64 Figure 52 – Typical isolated BMS in electric vehicle……………………………
66
Figure 53 – High voltage interlock system………………………………………
67
Chapter 03 Figure 54 – Power and energy comparison………………………………………
70
Figure 55 – typical battery management structure……………………………….
71
Figure 56 – Battery management system architecture design…………………… 73 Figure 57 – Cell voltage charge according to different temperatures……………
80
Figure 58 – Cell voltage charge according to different voltage rates……………
81
Figure 59 – Pulse charging and discharging D1T and D2T duty cycle…………..
84
Figure 60 – Transferring energy between cells………………………………….
87
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Chapter 04 Figure 61 – Battery management system architecture design…………………...
95
Figure 62 – Sample battery management system architecture…………………...
97
Figure 63 – Voltage divider based microcontroller voltage measuring………….
98
Figure 64 – Op-amp comparator based voltage sensor…………………………..
100
Figure 65 – Voltage sensor simulation…………………………………………... 101 Figure 66 – Voltage sensing system in the battery model……………………….. 102 Figure 67 – Current sensing IC ACS 712………………………………………... 104 Figure 68 – Current sensor module ACS 712……………………………………
104
Figure 69 – ACS 712 current sensor connections………………………………... 106 Figure 70 – LM35 temperature sensor connections to the processor……………. 109 Figure 71 – L293D motor controller connections with the atmega 2560………... 111 Figure 72 – Change in PWM signal according to duty cycle……………………. 112 Figure 73 – Connection of MOSFETs in the balancing circuit………………….. 115 Figure 74 – Graph of gain current vs the drain source voltage…………………... 117 Figure 75 – Graph of gain current vs the gate source voltage…………………… 117 Figure 76 – Optocoupler wiring circuit………………………………………….. 120 Figure 77 – Optocoupler simulation circuit…………………………………….... 121 Figure 78 – Optocoupler simulation for 2Hz input signal……………………….. 122 Figure 79 – Optocoupler simulation for 200Hz input signal…………………….. 122 Figure 80 – Optocoupler simulation for 2 kHz input signal……………………… 123 Figure 81 – Optocoupler simulation……………………………………………… 123 Figure 82 – Optocoupler simulation input current in signal generator…………... 124 ~k~
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Figure 83 – Amplifier design for the optocoupler……………………………….. 125 Figure 84 – Simulation results of the amplifier………………………………….
126
Figure 85 – Simulation circuit of the amplifier………………………………….
127
Figure 86 – Double-tiered switched capacitor circuit…………………………...
128
Figure 87 – capacitor charge with respect to the capacitor value……………….
129
Figure 88 – PWM signals of each group of MOSFETs………………………...
130
Figure 89 – Transferring cell energy vs cell voltage difference………………...
131
Figure 90 – Capacitor charge with respect to the capacitor value………………
132
Figure 91 – Operation of group 01 MOSFETs………………………………….
133
Figure 92 – Operation of group 02 MOSFETs………………………………….
135
Figure 93 – Full circuit of MOSFET connections with isolation part 1………...
136
Figure 94 – Full circuit of MOSFET connections with isolation part 2………...
137
Figure 95 – microcontroller connections for 4*20 LCD display………………..
139
Chapter 05 Figure 96 – Schematic design of the voltage measuring circuit………………...
143
Figure 97 – Circuit board design of the voltage measuring circuit……………..
143
Figure 98 – Top view of the voltage measuring circuit design…………………
144
Figure 99 – Bottom view of the voltage measuring circuit design……………...
144
Figure 100 – Schematic design of the cell balancing circuit…………………….
145
Figure 101 – Top view of the cell balancing PCB design……………………….
146
Figure 102 - Bottom view of the cell balancing PCB design……………………
146
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List of Tables Chapter 02 Table 01 – Battery Characteristics……………………………………………….
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Table 02 – State of charge of lead-acid battery………………………………….. 14 Table 03 – Development of Li-based battery system……………………………. 17 Table 04 – New battery trends…………………………………………………… 24 Table 05 – Typical Programming Values of Protection Circuit…………………. 65
Chapter 03 Table 06 – Cell balancing system comparison…………………………………... 75 Table 07 – comparison between SOC measuring method……………………….. 78 Table 08 – Applications and SOC measuring variables………………………….. 79
Chapter 04 Table 09 – Li-ion battery characteristics…………………………………………. 91 Table 10 – Li-ion high power battery characteristics…………………………….. 93 Table 11 – Operational temperature variation between electronic components…. 108 Table 12 – Fan speed variation for different temperature groups when charging... 113 Table 13 – Fan speed variation for different temperature groups when discharging 114 Table 14 – Comparison of MOSFET characteristics……………………………... 119 Table 15 – Capacity voltage difference when balancing…………………………. 134 Table 16 – Operating voltage of different modules………………………………. 140
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Introduction
Chapter 01
Introduction
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Introduction
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1.0 Introduction Most of the transport system in the world rely on fossil fuels hence combustion engine is the main power source of it. Fossil fuel is extracted from the earth however it is a limited resource. Burning fossil fuel does a lot of harm to the nature. Since most all fuel is from oil products or natural gas, vehicles too account for a substantial amount of worldwide release of CO2, the main greenhouse gas (Schipper, 2011). Motor vehicles emit 14% of the global CO2 and 50-60% of the CO, HC and Lead, 30% of the NOx and about 10-20% of the particulate emissions (Sagar, 1995). It pollutes the air mainly and also it is a major cause for climate change. As a result of this climate change and air pollution, electric vehicles received most attention. California had passed a law in 1998 stating that 2% of the cars sold by any manufacturer in the state be zero-emission vehicles, increasing progressively to 10% by 2003 (Sagar, 1995).
Crude Oil Imports - Unit Price Movements 160
Pice per barrel (USD)
140 120 100 80 60 40 20 0 1970
1975
1980
1985
1990
1995
2000
2005
Year
Figure 01 Crude Oil Price Variation (LLC, 2010)
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Fossil fuel price had increased slightly in recent years and in future the price won’t be able to control. Also the fossil fuel consumption over the last 26 years have a vast increment and the remaining fuel resources can be diminished after 2030 (Shafiee and Topal, 2009). So automobile manufacturers are developing alternative power vehicles such as Hybrid electric vehicles and full electric vehicles to overcome this problem. Electric vehicles have some popularity among vehicle owners today because of zero pollution and the low noise. Most of car manufactures in the world trend to make electric vehicles now. ‘Tesla’ company is a full electric car company and their car models have a great attraction among people. Most of the EV’s are manufactured to use in domestic life. Because of the battery capacity, maximum distance can be travelled per one charging cycles is limited to around 100-300 km. It is a major drawback of electric vehicles when we comparing combustion engines. So the battery technology has to be developed finding a right battery that has a high energy storage, low cost and weight and quick rechargeable (Sagar, 1995). Today the battery technology has developed in a significant amount but the travelling range of the vehicle is still behind to the Combustion vehicles. How about using EV technology to make electric racing cars. ‘BMW’, ‘BENZ’ and ‘Formula’ companies are making their electric sports cars now. Eg : BMW i8 , Formula electric and Benz sls electric So we came up with an idea of making a track day electric vehicle as our project. So we create a team and each member has a different section of the electric car to carry out. This research is about the battery management system of a track day electric vehicle. This research is carried out to maximize the efficiency of the battery management system of a track day electric vehicle and a sample battery pack will be used to demonstrate the methods.
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Battery or power storage of an electric vehicle is a main part of the car hence the travelling distance is depending on the battery capacitance and with the methodology of the battery management system is made. Power regenerative braking system is the system that regenerated the power while braking. But the energy can be stored by regenerative breaking is limited because of various reasons. Power loss is a major problem; we cannot entirely remove the power loss from it but can be controlled by monitoring some variables such as temperature. Regenerative energy is an instantaneous power. So it is difficult to store all the regenerative energy in batteries also batteries have limited charging and discharging cycles therefore storing regenerative energy in batteries will reduce the battery life. So another method of power storing must be added to store regenerative energy. Capacitors can store instantaneous energy. When the capacitance increases the amount of energy can be stored is also increased. Normal capacitors that used in electric systems has low capacitance and they self-discharged rapidly. There is another type of high power capacitors known as super capacitors and they have high capacitance and the energy loss is lower than the regular capacitors. Therefore, super capacitors are going to be used as the alternative power storage. Capacitors does not have moving parts so energy loss will limit but self-discharging can be happened if the energy has stored too long. Several possible methods of improving range and battery balancing techniques have examined in the literature survey.
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Introduction
Figure 02 A track day racing car
Figure 03 Benz SLS electric car
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Literature Review
Chapter 02
Literature Review
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2.0 Literature Review 2.1 Electric Vehicle Operation The vehicles emitting organic compounds, Pd, nitrogen oxide and carbon monoxide have done significant pollution of air. World population is growing by an extremely high rate so that the vehicle usage is also rising with the rise of the population. Fossil fuel is the main energy resource of these vehicles. In 21th century oil production reached a peak. Estimates indicate that petroleum and natural gas will be run out by the year 2042 (Shafiee and Topal, 2009). After inventing the lead acid batteries and the electric motors in late 1800s, the first electric vehicles were invented. In the early 1900s, electric vehicles were very popular and that time is called the golden period of electric vehicles. After the arriving of gasoline powered vehicles almost every electric vehicle was disappeared due to limitation of range, long charging time, heavy weight and poor durability of batteries (Young, Wang, and Wang, 2013) (Kulkarni, Kapoor, and Arora, 2015). Because of gas emission laws and air pollution automobile manufactures were forced to manufacture low carbon emission vehicles so the electric vehicle manufacturing is increasing today (Sagar, 1995) (Kulkarni, Kapoor, and Arora, 2015). Electric vehicles present an excellent alternative to the current fossil fuel powered vehicles due to several reasons. Low noise and zero emission are some main reasons why people buy electric car now days. Electric vehicles are perfectly suitable for urban environment thus they are very compact, not as wasteful as internal combustion engines in traffic and the limited range is not a matter in the urban environment (Sagar, 1995). Internal operation of electric vehicles is similar to the internal combustion vehicles. Like in combustion vehicles, electric vehicles have an electric motor, an ECM, a battery, battery management system with regenerative braking system a charger and a cooling and heating system.
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There are two types of motors used in electric vehicles AC motors, and DC motors. DC motors are easily control when comparing with AC motors and also less expensive than AC motors. However, DC motors are larger and heavier than the AC motors. Hence the electric motors have high torque acceleration of an electric vehicle is quicker than the internal combustion engine. That property can use to build fast electric racing cars because in races instant torque is much help full. Electric vehicle also has a feature called regenerative breaking and by using that feature the vehicle can generate electricity by own kinetic energy that can be stored in super capacitors. Electric vehicles sales are increasing rapidly when we compare the sales data for previous years. That shows that the demand for electric vehicles are higher now days. With the rise of the demand, much more research must be done to develop the EV technology.
Figure 04 Global EV sales
(The electric vehicle world sales database, 2016)
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2.2 Available Battery Varieties for EV’s A cell of a battery is consisting of an anode and a cathode and all the chemical process happen between those two. Other than the electrodes a battery has separators, terminals, electrolyte and a case (Dhameja and Dhameja, 2000).
A battery has one negative terminal and a one positive terminal. The electrolyte can be a gel, solid or liquid according to the battery type and it can be acidic or alkaline (Dhameja and Dhameja, 2000).
For an example electrolyte of a lead-acid battery is sulphuric acid and the negative terminal is made by pure lead and the positive terminal is made by lead-dioxide.
In late 80’s there were electric vehicles but failed, in early 90’s due to lack of battery technology (Kulkarni, Kapoor, and Arora, 2015). Nevertheless, in 1990s due to climate change governments looked forward to develop electric vehicle. For example, the U.S. Advanced battery consortium (USABC) was formed to develop electric vehicle batteries (Dhameja and Dhameja, 2000). Therefore, the electric vehicle battery technology was developed up to now passing so many stages.
Electric vehicle batteries should have some special properties rather than the normal batteries like laptop and cell phone batteries.
The battery should have high energy density to travel long range. The battery should give a stable output with different acceleration and it should have a higher C rate. Long life cycle is more important for electric vehicle battery and the maintenance cost also should be low. Also the battery must be environmental friendly and recycling must be possible (Dhameja and Dhameja, 2000).
Battery characteristic of some batteries displayed in below table. Referring the table, we can see that Li-polymer has the highest energy density with respect to the Li-ion but considering the battery safety Li-polymer is dangerous to use in electric vehicle because in a collision the battery can be exploded. ~9~
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Super capacitors are also a good type of an energy storage although the self-discharging characteristic is quite high in capacitors it cannot be used as electric vehicle energy storage. Capacitors can store instantaneous energy so they can be used to store the regenerative energy of the car.
Energy
Energy
Power
Efficiency
Density
Density
(%)
(Wh/kg)
(W/kg)
Lead-acid
70 - 80
20 – 35
Ni-Cd
60 – 90
NI-MH Li-ion
Type
Li-polymer
Fuel Cell Super Capacitors
Cycle life
Self-
(Cycles)
discharge
25
200 – 2000
Low
40 – 60
140 – 180
500 – 2000
Low
50 – 80
60 – 80
220
3000
High
70 – 85
100 – 200
360
70
200
250 – 1000
50 - 80
250 - 350
800 – 1200
95
0.3 – 0.5
2500
More than 2000 More than 1200 More than 2000 More than 30 000
Medium
Medium
Negligible
high
Table 01 Battery Characteristics
(Birke, Keller, and Prague, 2010), (Dhameja and Dhameja, 2000) & (Ehsani et al., 2004)
Under development of EV technology today many batteries are used gel, paste or resin as the electrolyte. Future batteries may have different chemistry than present batteries but the temperature effects will be their also. Every battery has an operating temperature range and when discharging or charging battery temperature rise. If we can minimize the temperature of batteries a large energy can be saved.
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There are a vast range of EV vehicle battery available on the market. Most of the electric vehicle manufacturers are using Li-ion or Ni-MH batteries for their EV’s. Normally NiMH battery is used in electric vehicles as a secondary power source. Ni-MH batteries are safer than the Li-ion battery but Li-ion is preferred as the power source of electric vehicles (Kulkarni, Kapoor, and Arora, 2015). In the literature survey, we are going to discuss characteristics of some battery type that can use as electric vehicle batteries. They are listed as follows, 1. Lead-acid battery 2. Lithium ion battery (Li-ion) 3. Nickel metal hydride battery (NI-MH) 4. Lithium polymer battery (Li-Po) 5. Fuel cell technology
2.2.1 Lead-acid Battery Lead-acid batteries, while the most widely used type in automobiles for over a century, have lower energy density when compared to other more modern battery types (Dhameja and Dhameja, 2000).
Lead acid batteries are significantly cheaper than the other battery types. There are four types of lead-acid batteries available on the market (Cary R. Spitzer and Vutetakis, 2008). i. Flooded battery.
This is the traditional lead-acid battery. In this type of a battery liquid electrolyte is free to move in the cell compartment.
Can add distilled water as the battery dries out by accessing to the individual cells.
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ii. Sealed battery.
This is seal type of battery and the user doesn’t have access to cells. This battery is only a slight modification of the flooded lead-acid battery.
iii. Valve regulated lead-acid battery. (VRLA)
This is also a sealed type battery and by the valve regulating mechanism allow hydrogen and oxygen to outflow safely while charging.
iv. Absorbed glass matte battery. (AGM)
The charging and discharging efficiencies have increased in this type of lead-acid batteries by the absorbed glass matte construction theory.
This type of batteries are now using for power sport and in many engine start applications.
Lead and lead-dioxide are good electric conductors so they are taken as the anode and the cathode of the lead-acid battery respectively. As the electrolyte Sulphuric acid and the water is used. During charging water in the electrolyte solution is broken down by electrolysis. Connection of an electrical power source forces electrons to flow from positive to negative. The cathodic and anodic reactions are expressed as follows (Cary R. Spitzer and Vutetakis, 2008), (Lecture: Lead-acid batteries how batteries work conduction mechanisms development of voltage at plates charging, discharging, and state of charge key equations and models, 2009).
-
At the anode 𝑃𝑏𝑆𝑂4 + 2𝐻 + + 2𝑒 − → 𝑃𝑏 + 𝐻2 𝑆𝑂4
-
At the cathode 𝑃𝑏𝑆𝑂4 + 2𝐻2 𝑂 → 𝑃𝑏𝑂2 + 𝐻2 𝑆𝑂4 + 2𝐻 + + 2𝑒 −
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Figure 05 The Traditional Pb-acid battery
During discharge electrons move from negative electrode Positive electrode through an external load. This process reduces the charge and the voltages at the electrodes. When the battery is discharged, a coating can see around the surfaces of two electrodes. The cathodic and anodic reactions when discharging displayed below (Lecture: Lead-acid batteries how batteries work conduction mechanisms development of voltage at plates charging, discharging, and state of charge key equations and models, 2009). -
At the anode 𝑃𝑏 + 𝐻2 𝑆𝑂4 → 𝑃𝑏𝑆𝑂4 + 2𝐻 + + 2𝑒
-
This reaction releases 𝐸 0 = 0.356 𝑒𝑉 of energy
At the cathode 𝑃𝑏𝑂2 + 𝐻2 𝑆𝑂4 + 2𝐻 + + 2𝑒 − → 𝑃𝑏𝑆𝑂4 + 2𝐻2 𝑂
This reaction releases a net energy of 𝐸 0 = 1.685 𝑒𝑉
Voltage of the battery cell depends on the temperature. So at the 298 oK the battery cell voltage of a lead-acid battery is, 𝑉𝑜𝑐 = 0.356 + 1.685 = 2.041 𝑉
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Full Charged
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Completely Discharged
100 %
0%
0%
100 %
Electrolyte concentration, Q
~ 6 moldm-3
~ moldm-3
Electrolyte specific gravity
~ 1.3
~ 1.1
12.7 V
11.7 V
State of charge(SOC) Depth of discharge
No load voltage at 25 oC
Table 02 State of charge of the battery (Lecture: Lead-acid batteries how batteries work conduction mechanisms development of voltage at plates charging, discharging, and state of charge key equations and models, 2009)
When a lead-acid battery discharge at some point the electrode sulfation builds where it becomes difficult to recharge. So battery should not be over discharged.
Figure 06 Battery molality vs battery cell voltage (Lecture: Lead-acid batteries how batteries work conduction mechanisms development of voltage at plates charging, discharging, and state of charge key equations and models, 2009)
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Normally lead-acid batteries are rated at room temperature and operates well around this temperature. Low temperatures result in performance decline while high temperature cause shortened in battery life. Typically, the lower operating temperature of the lead-acid battery is -40 oC and the upper temperature range is 50 to 60 oC (Cary R. Spitzer and Vutetakis, 2008).
Figure 07 Power vs temperature
2.2.2 Lithium-ion Battery ‘Lithium is the metal with highest negative sub-atomic particles and lowest atomic weight’ (Dhameja and Dhameja, 2000).
Lithium metal is a highly reactive metal with air and most liquid electrolytes. So graphitic carbon intercalated with Lithium metal are used (Dhameja and Dhameja, 2000).
Lithium-ion and NiMH batteries produced equivalent amount of energy. But rather than NiMH batteries Lithium-ion batteries are smaller and half weight. Charging and discharging of Li-ion batteries typically faster than Pb-acid and NiMH batteries (Dhameja and Dhameja, 2000).
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Li-ion cells available in market today have the highest energy and power density and their performance is also better than the other available batteries. There are four types of cells available in the market considering the shape. They are small and large cylindrical shape, prismatic and pouch (Andrea, 2010).
Figure 08 Li-ion battery varieties
(Andrea, 2010)
As the anode material carbon, particularly graphite and hydrogen-containing carbon materials are generally used. Cobalt, Nickel and manganese are used usually as the cathode material but cobalt oxide is the material which is preferred by technically (Dhameja and Dhameja, 2000). For the electrolyte liquid material is used contain with lithium hexafluoro-phosphate. Nominal voltage, energy and power density varies with the using materials and their chemistry. Liquid Li-ion batteries were in the global market for several years then in 1995 the solid state Li-ion batteries were introduced. Then the energy density increased up to 100Whr/kg and the operating temperature also increased -20 oC to 60 oC (Dhameja and Dhameja, 2000). By modifying a special manganese oxide spinel structure with a specific capacity almost equal to the cobalt oxide spinal a battery has developed with a specific energy of 115 Whr/kg and with a 60 Ahr rate.
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Year
Literature Review
Cathode
Anode
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Electrolyte
Battery system
1980 – 1990 1990 – 2000
LiWO2 LiC6
LiCoO2, LiNiO2
Li/MoO2, Polymer
LiMn2O4
LiVOx C/LiMn2O4
Table 03 Development of LI-based battery system
(Dhameja and Dhameja, 2000)
Li-ion cells should be operated with in a safe operating voltage range and if the limitation are exceeded the battery can be damaged, also fire will generate. So to avoid damage and fire Li-ion cells should not charge exceeding the save voltage limit or discharge beneath the limited voltage. Also the cells should be operated between the given temperature range to increase the life time (Andrea, 2010).
Figure 09 Safe operating area charging and discharging
(Andrea, 2010)
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Figure 10 Charging and Discharging of Li-ion batteries
(Andrea, 2010)
Normally Li-ion cells are discharged in constant current. Without damaging the cell, Liion can discharge to 20% of SOC by a constant current rate but after that, the discharging should do by using constant voltage. Charging voltage is large than the discharging voltage generally and because of that all charging energy does not involve when discharging. The electrochemistry of the Li-ion battery on charging shown below (Dhameja and Dhameja, 2000).
-
At the negative electrode 𝐿𝑖𝑥 𝐶6 + 𝑥𝐿𝑖 + + 𝑥𝑒 − → 𝐿𝑖𝐶6
-
At the positive electrode 𝐿𝑖𝐶𝑜𝑂2 → 𝑥𝐿𝑖 + 𝑥𝑒 − + 𝐿𝑖(1 − 𝑥)𝐶𝑜𝑂2
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The electrochemistry of discharge as follows (Dhameja and Dhameja, 2000).
-
At the negative electrode 𝐿𝑖𝐶6 → 𝐿𝑖𝑥 𝐶6 + 𝑥𝐿𝑖 + + 𝑥𝑒 −
-
At the positive electrode 𝑥𝐿𝑖 + 𝑥𝑒 − + 𝐿𝑖(1 − 𝑥)𝐶𝑜𝑂2 → 𝐿𝑖𝐶𝑜𝑂2
2.2.3 Nickel Metal Hydride Battery Ni-MH battery came to use from 1950s, until now it has developed dramatically, passing decades. Ni-MH batteries are widely used for laptops, camcorders and mobile phones. However, today over 95% of HEV’s are using Ni-MH batteries because they have low maintenance cost, design flexibility, High power and energy density. In addition, Ni-MH batteries are safer than Li-ion batteries. Nevertheless, for electric vehicles Li-ion are most preferred than the Ni-MH because of fast charging (Kulkarni, Kapoor, and Arora, 2015). General characteristics of a Ni-MH battery listed as follows (Hydride, 2013). i.
Can be recharged around hundred times.
ii.
Efficient at high rate discharges.
iii.
Has higher capacity than nickel-cadmium batteries.
iv.
The life expectancy would be about 2 – 5 years.
v.
Operates well at a wide range of temperatures. 0 oC to 50 oC temperature range for both charging and discharging.
The electrochemistry of the Ni-MH battery on charging shown below (Hydride, 2013). -
At the negative electrode 𝐴𝑙𝑙𝑜𝑦 + 𝐻2 𝑂 + 𝑒 ↔ 𝐴𝑙𝑙𝑜𝑦 (𝐻) + 𝑂𝐻 −
-
At the positive electrode 𝑁𝑖(𝑂𝐻)2 + 𝑂𝐻 − ↔ 𝑁𝑖𝑂𝑂𝐻 + 𝐻2 𝑂 + 𝑒
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The electrochemistry of discharge as follows (Hydride, 2013). -
At the negative electrode 𝐴𝑙𝑙𝑜𝑦(𝐻) + 𝑂𝐻 − ↔ 𝐴𝑙𝑙𝑜𝑦 + 𝐻2 𝑂 + 𝑒
-
At the positive electrode 𝑁𝑖𝑂𝑂𝐻 + 𝐻2 𝑂 + 𝑒 ↔ 𝑁𝑖(𝑂𝐻)2 + 𝑂𝐻 −
Electrolyte of nickel-metal hydride battery is alkaline. As the separator to allow efficient ionic diffusion non-woven polyolefin is used.
2.2.4 Lithium Polymer Battery Li-Polymer batteries placed in fourth as electric vehicle batteries. Nevertheless, because of safety purposes Li-polymer batteries are not use for commercial purpose. Anodes of the Li-Po battery made of using Lithium or Carbon intercalated with Lithium. The battery chemistry of Li-Po has increase the specific energy and power of the Lipolymer battery than other available bateries. Because of the battery electrode’s kinetics, the ability to absorb and release ions have limited the specific power and the life cycle (Dhameja and Dhameja, 2000). Electrochemistry of the Li-Polymer battery displayed as follows.
-
Cathodic reaction when charging and discharging 𝐿𝑖𝑥 𝑀𝑋 ↔ ∆𝑥𝐿𝑖 + + ∆𝑥𝑒 − + 𝐿𝑖𝑥−∆𝑥 𝑀𝑋
-
Anodic reaction When charging and discharging 𝐶6 + ∆𝑥𝐿𝑖 + + ∆𝑥𝑒 − ↔ 𝐿𝑖∆𝑥 𝐶6
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2.2.5 Fuel Cell Technology Sir William Graves was the first demonstrator of the fuel cell technology. It dates back to 1839. Experiments on fuel cell vehicles have been conducted for the past 4 decades, with some working prototypes demonstrated as far back as mid 1960’s. Fuel cells have much promise in being the leading energy storage system of the future automobiles. Rather than Li-ion electric vehicles in fuel cell vehicles there are some advantages (Thomas, 2009). 1. Less weight 2. Required a smaller amount of space 3. Limited generation of greenhouse gases 4. Low cost 5. Refueling time is reduced
‘The reversible electrochemical reaction for the electrolysis water is the basic principle of fuel cell technology’ (Dhameja and Dhameja, 2000). 𝑊𝑎𝑡𝑒𝑟 + 𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ↔ 2𝐻2 + 𝑂2 The basic concept of fuel cell technology as follows. ‘Hydrogen gas is supplied to the anode and reacts electrochemically at the electrode surface to form protons and electrons’ (Dhameja and Dhameja, 2000). These electrons travel through the connecting rods to the cathode, reacts with the oxygen, and previously formed protons to form water. The reactions at the anode and cathode expressed as follows (Dhameja and Dhameja, 2000). -
At the anode 2𝐻2 → 2𝐻 + + 2𝑒 −
-
At the cathode 𝑂2 + 4𝐻 + + 4𝑒 − → 2𝐻2 𝑂
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In the fuel cells, the operating fuel not only the hydrogen. As output in fuel cell, only water and electricity generate. Therefore, the process is ecofriendly. 𝐹𝑢𝑒𝑙 + 𝑜𝑥𝑖𝑑𝑒𝑛𝑡𝑠 → 𝐻2 𝑂 + 𝑂𝑡ℎ𝑒𝑟 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 + 𝑒𝑙𝑒𝑐𝑡𝑡𝑟𝑖𝑐𝑖𝑡𝑦 Several single fuel cells are connected series or parallel to form a fuel cell battery to achieve different voltages, currents and power.
Figure 11 Basic fuel cell battery (Ehsani et al., 2004)
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2.3 Future Batteries To meet the energy requirements compete with the energy crisis in the future the electric vehicle batteries must developed to be similar to the fossil fuel. High energy density, High current density and wide range of temperature must be there in the future electric vehicle batteries along with the cost of the batteries being reduced.
Figure 12 Future and present Li-ion battery cells (Birke, Keller, and Prague, 2010)
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New battery Lithium + sulfur
Lithium + Fluorine
Literature Review
Negative
Positive
Electrode
Electrode
Lithium
Sulphur
Metal
with Carbon
Lithium
MexFy
Metal
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Electrolyte
Challenges
Organic based
Safety & life time
Solid state
High temperature
polymer
required
Perfect
material
distribution in the atomic structure
Lithium + Air
Composite
Li & Ni
carbon
plates
Solid polymer
Table 04 New Battery trends (Birke, Keller, and Prague, 2010)
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Life safety
time
&
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2.4 Modelling of a battery Every battery has an internal resistance and with the time pass the internal resistance of the battery increases because of its battery chemistry. Anodic and cathodic reaction happen between batteries negative and positive terminals and sometime substance might deposited. In addition, the reacting materials could be dead. That can affect the increment of the batteries internal resistance. The simplest model of a battery can write as following, 𝑉 = 𝐸 − 𝐼𝑅 V is the open circuit voltage of the battery. E is the rated capacity of battery. I and R is the current flow through the battery and the internal resistance of the battery respectively.
Figure 13 Cell resistance, cell capacity varying with the time
(Andrea, 2010)
The actual cell model is more complex than the simple modelling of the battery. For different state of charge values batteries have different voltages. Also with the temperature, the cell voltage is varying. For large variations of the discharge current, also the cell voltage is varying. Battery aging is also affect the battery voltage.
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A battery has two types of resistances ohmic resistance and the ionic resistance. Therefore, the battery model should include those also. The following diagram explains how the battery voltage and current varying according to different states of the battery.
Figure 14 Various models of the battery
(Andrea, 2010)
In part (a), has shown a simplest battery model with a constant internal resistance and for that model battery voltage is varying linearly. In the part (b) the battery is modeled with relaxation RC circuit. Battery voltage is dropping with the time it is similar to the real battery model but not equal. Then in part (c) has shown the RC circuit with the AC impedance (Andrea, 2010). The Real battery model contain all above describe three models. So a similar model has implemented in part (d) with both internal ohmic resistance and the AC impedance.
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Figure 15 Equivalent model for a single cell (Zhang and Sisk, 2013)
Cell equivalent equation can be derived by using the above circuit model and the equation is displayed below. Vt is the terminal voltage of the battery. The battery current I(t) is positive for discharging and negative when charging (Zhang and Sisk, 2013).
𝑉𝑡 (𝑡) = 𝐸0 (𝑡) − 𝑅0 𝐼(𝑡) − 𝑉𝑐1 (𝑡) − 𝑉𝑐2 (𝑡)
Vc1 and Vc2 are the voltage across the capacitors and that can be derived by using the characteristics of the RC circuit. The derived equation displayed as follows (Zhang and Sisk, 2013). 𝑉𝑐 (𝑡) = 𝑉𝑐 (𝑡0 ) × 𝑒 −𝛽(𝑡−𝑡0 ) +
𝛽=
𝛾𝐼(𝑡) (1 − 𝑒 −𝛽(𝑡−𝑡0 ) ) 𝛽
1 1 𝑎𝑛𝑑 𝛾 = 𝑅𝐶 𝐶
According to that the battery terminal voltage can be written as follows (Zhang and Sisk, 2013),
𝑉𝑡 (𝑡) = 𝐸0 (𝑡0 ) − 𝑉𝑐1 × 𝑒 −𝛽1 (𝑡−𝑡0 ) − 𝑉𝑐2 × 𝑒 −𝛽2 (𝑡−𝑡0 ) 𝛾1 𝛾2 + 𝐼(𝑡) (−𝑅0 − (1 − 𝑒 −𝛽1 (𝑡−𝑡0 ) ) − (1 − 𝑒 −𝛽2(𝑡−𝑡0 ) ) ) 𝛽1 𝛽2
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2.5 Battery Management System Architectures Battery management system is an essential system in every battery operated electric item like laptop computers, mobile phones and most important in electric vehicles. Batteries has various characteristic and with the outside condition of batteries they are react in various ways. Sometimes it is dangerous so the batteries should be monitored and controlled to avoid the damage to the electric equipment and also to the person who using it. Battery is the main power source uses in electric vehicles. Therefore, the energy stored in the batteries should be managed properly to maximize the range of the vehicle. In an electric vehicle, there are about 100’s of batteries. If one battery get a fault, it would affect the whole system. So in an electric vehicle, battery management system is needed for following main reasons (Xing et al., 2011). 1.
Maintain the safety and the reliability of the battery
2.
Battery sate monitoring and evaluation
3.
To control the charge
4.
For balancing cells controlling the operating temperature
5.
Management of regenerative energy
Battery management systems are equipped with some sensors to determine several factors like very battery cells terminal voltage, state of charge of the battery, the temperature of batteries etc. Therefore, battery management system can be divided into some sub systems and some sub circuits. Some circuit are control the system while some are sensing and some are for the safety purpose.
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A comprehensive battery management system should have the following functionalities (Xing et al., 2011). 1. Data acquisition 2. Safety protection 3. Sate of the battery determination 4. Controlling of battery charging and discharging 5. Cell balancing 6. Thermal management 7. Sending information about the battery status and authentication to the user interface 8. Communication between each battery component 9. Extending the battery life 10. Regenerative energy management
Figure 16 Battery management subsystems (Lu et al., 2013)
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The battery management systems performance rely on the communication between each system. It should be fast, and every subsystem should operate accurately because all information generated are so sensitive and with a small error, there could be a large damage. A functionality of a sample battery management system has shown below.
Figure 17 Battery management system signal flow chart (Xing et al., 2011)
The battery management system is a combination of hardware component and a software. State of charge (SOC) determination, state of health determination, cell balancing control, fault detection and communication with the user interface is done by using the software. All the functions are mathematically calculated along to the fed equations. Software is programmed to a microcontroller when the system is implementing. In the hardware system, typically there are safety circuits, sensor system, Controlling circuits and communication circuits (Lu et al., 2013), (Xing et al., 2011).
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When we considering the battery management system hardware there are three kind of topologies that are using presently. They are categories as centralized, distributed and modular structures (Xing et al., 2011).
According to steinhorst et al., 2016 recent battery management system structures can be divided into to two as state of art /distributed architectures and centralized structures.
Figure 18 Battery management system architectures (Steinhorst et al., 2016)
In centralizes static battery balancing system method voltage and the temperature of cells are measured also the current through the battery stack also measured by using Hall Effect current sensors. Sensing and balancing modules (SBM) are installed in each individual cell or in each cell pack. A master controller controls sensing and balancing modules. Higher voltage cells are reduced to match with the lowest voltage cells. But most of centralized static architectures uses passive cell balancing methods (Steinhorst et al., 2016).
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In distributed static BMS method a master controller is not there and the controlling is divided through the whole system. Each cell or cell pack contains with an individual microcontroller to control those. All the sensing is done in those. Those controllers are communicated with each other and determined which cell or cell group to discharge. Expanding is easier because there is no changes in hardware or software. The main disadvantage of this type is communication between the each controllers result to some increase in balancing time. Cost also high because the circuits should be manufactured efficiently (Steinhorst et al., 2016). Centralized reconfigurable BMS has a main controller to control the cells. In this method, there is a specialty the series connected cells are connected in parallel to balance. This method does not need intelligence control. Cell lifetime is affected by centralized control but battery balancing discharged rate is reduced (Steinhorst et al., 2016). As in the centralized reconfigurable structure, in the distributed reconfigurable method uses the same cell balancing operation. Rather than the main controller, distributive reconfigurable structure has separate microcontrollers to control and monitor cells.
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2.6 Battery Cell Balancing Methods Batteries are used in different applications, for various power needs, low power to high power applications. To satisfy those energy needs batteries are used. To get various power needs they are connected parallel or series. The parallel connections are easy to handle and balance because batteries are collectively formed a one big cell and no need of cell balancing because of self-balancing capability. Because of the equal terminal voltage, current flow according to the each cells internal impedance and it allows the cells to be balanced (Einhorn, Roessler, and Fleig, 2011). However, in series connected battery cells cannot perform like that so additional equalization method has to be used. There are over charging methods to discharge energy from the series connected cell pack but for electric vehicle batteries, it cannot be used because EV’s need high-energy efficiency (Moore and Schneider, 2001). Mostly in electric vehicle applications, Li-ion batteries are used. Over charging or over discharging of Li-ion cells could damage the electric system. In addition, it will cause to high safety issue (Einhorn, Roessler, and Fleig, 2011). So especially in electric vehicles, cells balancing is critically important. With over the time individual cell voltages will drop and the battery pack capacity decreased. Therefore, without the balancing function the whole battery system will fail (Daowd et al., 2011). In series connected battery packs capacity depends on the weakest cell in the cell pack. If that weakest cell is fully charged, charging of the battery pack cannot be carry on. Again, if that weakest cell is fully discharged the remaining charge of the battery pack cannot obtain (Einhorn, Roessler, and Fleig, 2011). “Cell balancing is useful to control the higher voltage cells until the rest of the cells can catch up” (Moore and Schneider, 2001). Therefore, finally we can say that the battery balancing is needed for the health, safety, available capacity and life of the series battery stack (Li, Mi, and Zhang, 2013).
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Cells can be imbalanced because of various reasons it can be a manufacturing problem or a functioning problem. Mainly changes between cells happens due to two reasons changes in internal impedance or cell capacity reduction (Moore and Schneider, 2001). In manufacturing process of batteries due to economical limitations and technical problems battery capacities vary. That is due to internal impedance changes. When making a battery pack cells are arranged together. When operating cells can have deferent temperatures even there is a good heating or cooling system. Therefore due to temperature differences battery capacities might be different (Einhorn, Roessler, and Fleig, 2011) (Daowd et al., 2011). The performance of the battery pack with different cell amounts can be maximized and equalized by an electronic circuit module called, the battery balancing unit (Einhorn, Roessler, and Fleig, 2011). There are two types of cell balancing methods are available. They are energy recovering method and the energy dissipation method (Li, Mi, and Zhang, 2013). Typically called as the active cell balancing and passive cell balancing respectively (Einhorn, Roessler, and Fleig, 2011). In energy dissipation or passive cell balancing method energy of fully charged cells dissipated by using a resister or a transistor. The excessive charge of batteries emit as heat through resistors or transistors. Therefore, balancing current is limited due to heat (Li, Mi, and Zhang, 2013). In this type of balancing circuits, because the energy is emitted as heat, the balancing efficiency is zero (Li, Mi, and Zhang, 2013) (Einhorn, Roessler, and Fleig, 2011). In active cell balancing or energy recovering method the excess energy that have in fully charged cells distributed among low charged cell or cells. This process is done by using short time storage elements such as capacitors, inductive component and controlling switches or converters (Daowd et al., 2011) (Einhorn, Roessler, and Fleig, 2011) (Li, Mi, and Zhang, 2013) (Moore and Schneider, 2001).
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Below diagram shows different active and passive battery balancing topologies used for cell balancing.
Cell balancing
Passive Balancing
Fixed shunt resister
Active Balancing
Switching shunting resistor
Capacitor Base
Inducture or Transformer Base
Converter Base
Switched capacitor
Single or Multi inductor
Cuk Converter
Single switched capacitor
Single windings transformer
Flyback converter
Double-Tiered switched capacitor
Multi or Multiple windings transformer
Buck/Boost converter
Ramp Converter
Quasi-Resonate converter
Full-bridge converter
Figure 19 Battery cell balancing topologies (Daowd et al., 2011)
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The following figure shows how is cell balancing acting on the cells. There are three cells with different capacitance. Cell capacity is displayed as the cell size. With cell balancing cells are equally balanced.
Figure 20 Cell balancing comparison
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2.6.1 Passive Balancing Methods As shown on the there are two methods of passive balancing fixed resister method and control shunting resister method. In fixed resister method, resisters are connected to each cell and they are adjusted to limit battery voltages. Current is by passed from each cell and it can be used only in lead-acid and Ni-cd or Ni-MH batteries. The reason is higher voltage cells are kept over charging while other lower voltage cells are fully charged (Daowd et al., 2011).
A
Figure 21
Figure 22
Fixed resister cell balancing
Control shunting resister cell balancing
(Daowd et al., 2011)
(Moore and Schneider, 2001)
In control shunting method, each cell voltages are measured and the energy is discharged from high voltage cells. When comparing with the fixed resister based cell balancing method this method is efficient because of intelligent control. But the nergy is vast through resisters as heat (Daowd et al., 2011) (Moore and Schneider, 2001).
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2.6.2 Active Cell Balancing Methods. There are mainly three types of active cell balancing methods as mention in earlier. Capacitive shunting method uses capacitors to distribute excess cell energy through cell pack. In inductor or transformer based balancing method energy is transferred to another cell or group cells but in this type of balancing methods some disadvantages are there. The third method is energy converting method and this method is better than the other methods but the cost is high and high complexity. 2.6.2.1 Capacitive Shunting Cell Balancing There are three types of capacitive shunting cell balancing methods. They are switched capacitor, single switched capacitor and double-tiered capacitor (Daowd et al., 2011). There is another method called modularized switched capacitor in that method battery pack is divided into several packs and those packs are balanced by using switched capacitor method. Also each cell pack is balanced also using switched capacitor method (Daowd et al., 2013).
Figure 23
Figure 24
Modularized switched capacitor balancing
Switched capacitor cell balancing
(Daowd et al., 2013)
(Daowd et al., 2013)
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In switched capacitor method there are capacitors one less than the available cells and there are bi-directional switches two times of the available cell amount (Daowd et al., 2011) (Daowd et al., 2013). This method does not need intelligent control and it can be used in both charging and discharging. The main disadvantage of this method is long equalization time (Daowd et al., 2013) (Daowd et al., 2011). Single switched capacitor balancing method only uses a one capacitor to balance the battery stack but needs five more than the cell amount of switches to control the balancing cells. Battery capacities of cells are measured by the controller and turn on the required switches to flow excess energy to the highest charged cell to the lowest. This method is preferred to cells more than 4 because of the size and the cost of the system (Daowd et al., 2013) (Daowd et al., 2011).
Figure 25
Figure 26
Single switched capacitor cell balancing
Doubled-tiered switched capacitor cell balancing
(Daowd et al., 2013)
(Daowd et al., 2013)
In double-tiered switched capacitor uses two or more capacitor ties to shuttle the energy between cells. For n number of cells to form a double-tiered switched cell balancer needs n number of capacitors and 2n number of bi-directional switches.
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By including more capacitor tiered to the network can formed more paths between batteries and that means less impedance to travel energy between cells. In addition, it reduces the cell balancing time also. This type of cell balancing method can be used for both charging and discharging (Daowd et al., 2013) (Daowd et al., 2011). 2.6.2.2 Inductor/Transformer Cell Balancing Single/multi-inductor, single winding transformer and multi-winding transformer are the three methods that use available in inductor/transformer based cell balancing topology. It has smaller balancing execution time but have high cost and because of higher switching frequency have to use filtering capacitors across every battery (Daowd et al., 2011). 2.6.2.2.1 Single or Multi-inductor Cell Balancing In this balancing method, one or more inductors are used. In single inductor balancing method use only single inductor to distribute energy through the system. Cell voltages are sensed and by that, the controlling system determined which cell is to discharge and which to charge. This is done by controlling switches normally these switches are MOSFET’s (Daowd et al., 2011).
Figure 27
Figure 28
Single inductor cell balancing
Multi inductor cell balancing
(Daowd et al., 2011)
(Daowd et al., 2011)
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In multi inductor, topology n-1 inductors are used with n number of available cells. In this method, only neighboring cells are balanced. In here also energy discharged by a switching mechanism, MOSFET’s are controlled by a PWM signal and switch of the discharging cell is first turn on then the balancing cell (Daowd et al., 2011). 2.6.2.2.2 Single-Windings Transformer Cell Balancing Single winding transformer uses only one transformer. With the direction of energy transform, there are two types of single-winding called pack-to-cell topology and cell-topack topology. In pack-to-cell topology, the energy is carried from the energy source and transfer to the weakest cell or cells by operating switches (Daowd et al., 2011) (Moore and Schneider, 2001). In cell-to-pack method extra energy from charged cells transferred to the battery stack by using the transformer.
Figure 29 Pack-to-cell single-winding transformer cell balancing (Moore and Schneider, 2001)
2.6.2.2.3 Multi-Winding Transformer The multi-winding transformer method can be divided into two groups one is multiwinding transformer and the next is multiple transformer. In first method multi-winding transformer cells are connect to the multiple secondary winding of the transformer and the primary winding is connected to the battery pack. This also can be divided into two types considering the direction of the energy flow as flyback and forward structures (Daowd et al., 2011) (Zhi-Guo et al., 2006). ~ 41 ~
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In flyback method (figure 30) energy is transferred from the energy source through the primary side of the transformer when the switched on the primary side is on and off. The energy is flown into all cell but most to the lowest voltage (least resistance) cells. Diodes are attached to each multiple winding to control the current flow direction (Daowd et al., 2011) (Moore and Schneider, 2001) (Zhi-Guo et al., 2006). By forward structure (figure 31) each batteries voltage is sensed. The entire battery cell is connected to the secondary multi windings of the transformer with a MOSFET. With the voltage reading of cells, controller identified what are the highest voltage cells and they are discharged by controlling the MOSFETs attached to them. The excess energy is transferred to the battery stack through the primary winding of the transformer (Daowd et al., 2011) (Zhi-Guo et al., 2006).
Figure 30
Figure 31
Flyback cell balancing method
Forward cell balancing method
(Daowd et al., 2011) (Zhi-Guo et al., 2006)
(Daowd et al., 2011) (Zhi-Guo et al., 2006)
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In multiple transformer balancing method there are transformers to each cell. The energy from the energy source distributed to the lowest cell voltage batteries from primary winding to the secondary winding when the MOSFET connected to the all the primary winding turned on and off (Moore and Schneider, 2001).
Figure 32 Multiple transformer cell balancing (Moore and Schneider, 2001)
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2.6.2.3 Energy Converter Based Cell Balancing Energy converter based cell balancing systems can be categorized into six. They are cuk converter, buck or boost and buck/boost converter, flyback converter, ramp converter, full-bridge converter and quasi-resonator converter. 2.6.2.3.1 Cuk Converter Cell Balancing In cuk converter neighboring pair of cells are balanced by using two inductors, two switches and one capacitor. Energy is transferring between two neighboring cells so the balancing time is large and the balancing effectiveness is low (Daowd et al., 2011). Therefore, cuk converter is not suitable for larger cell packs. For n number of cells n1inductor MOSFET circuits required. The MOSFETs have to be controlled by a PWM signal (Daowd et al., 2011).
Figure 33 Multi inductor cell balancing (Daowd et al., 2011)
2.6.2.3.2 Buck, Boost or Buck/boost Converter (DC/DC) Cell Balancing This type of balancing methods are used in lot of applications. These are quite expensive and also complexity of the circuits are much higher than the other methods. Boost converters can removed extra energy from higher voltage cells and distributed among whole battery pack. Intelligent control is needed to control the boost converters. Several battery capacity measuring technics are used to operate switches (MOSFETs) such as voltage measurement and state of charge estimation (Daowd et al., 2011).
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Buck/boost converter is mostly used to transfer energy from higher voltage cells lower voltage cells. Controller is identified the cells’ status by monitoring voltage across each battery terminals. Then give required signals to MOSFETs (Daowd et al., 2011). However, step down and step up functions are useless at the same time.
Figure 34 DC/DC converter cell balancing methods (Zhi-Guo et al., 2006)
2.6.2.3.3 Flyback Converter Cell Balancing There are two types of flyback converters unidirectional and bidirectional. In unidirectional method, energy is stored in the transformer when the switch is on and that energy is transferred to the cells when the switch is off. In the bidirectional method energy can transferred power source to cells and also from high voltage cells to the battery pack (Daowd et al., 2011).
Figure 35 Bidirectional flyback converter cell balancing (Daowd et al., 2011)
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2.6.2.3.4 Ramp Converter Cell Balancing Ramp converter method is similar to the multi-winding transformer method. But rather than one secondary winding for each cell this type only needs one secondary winding for two cells. In ramp converter method, cells are balance according to an odd even method. Each lowest cell charging cycle is divided into two and balance the odd and even number of cells separately (Daowd et al., 2011).
Figure 36
Figure 37
Ramp converter cell balancing
Full-bridge cell balancing
(Daowd et al., 2011)
(Daowd et al., 2011)
2.6.2.3.5 Full-Bridge Converter Cell Balancing This type of cell balancing method is mainly for the plug-in hybrid electric vehicles. Complexity of the circuit is much higher and the cost of this type of cell balancing converters are quite high (Daowd et al., 2011). Intelligent control method has to be used to control MOSFET’s and to do that high performance control IC’s are needed.
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2.6.2.3.6 Quasi-Resonant Converter Cell Balancing There are two types of resonate controllers zero-current quasi-resonator and zero-voltage quasi-resonator. This type of balancing methods gives higher efficiency because the switching losses are negligible (Daowd et al., 2011). However, its controlling part is much more complex and the cost is high.
2.7 Battery Cell Balancing System Control Controlling of the battery balancing system is the main function of cell balancing system. Therefore, it should be accurate and fast. Microcontrollers are used to control the cell balancing system by measuring and taking actions. In centralized battery management system strategies, only one system controller a microcontroller is used. There are two or more microcontrollers in distributed battery management system strategies. The one microcontroller should be fast enough to control the full system or the cell pack. In electric cars, there are hundreds of batteries so those cannot be control using only one controller. There are slave controllers to control cell packs. They are monitored and controlled by the main controller. The micro-controllers main task is controlling the battery balancing switches. The microcontroller sense the battery voltage and control the switches to distribute excess charge of cells. 2.7.1 Available Controlling Switch Types There are various switch type available in power electronic industry. However, for the electric vehicle control special switches have to be used. They should have special properties. In electric vehicles high speed controlling is needed to operate cell-balancing circuits. Therefore, the operating switches should be high speed and also resist to high frequency. In addition, those switches should be last long because vehicles should be able to operate some years without repairing.
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When considering the power consumption the controlling switches must operate in low power range for the reason that is electric vehicles needs power efficiency. So considering those reasons electric vehicle manufactures use following switches as controlling switches. 1. Solid-state relay 2. Metal-oxide semiconductor field-effect transistor (MOSFET) MOSFETs are a type of field effect transistor and some characteristics are improved in MOSFETs than FET’s. 2.7.1.1 Solid-State Relay (SSR) Solid-state relays are operated without using mechanical movable parts as in mechanical relays. SSR can be operated by using small supply voltage. Solid-state relays are equipped with electronic components such as thyristors, triacs, diodes, MOSFET’s and a optical semiconductor (photocoupler). Input and the output of the relay is isolated by this photocoupler. An LED bulb to the photoelectrical device transmits the input signal and the output signal will give the response according to the input (Instruments, 2006), (Solidstate Relays application guide, 2002).
Figure 38 Solid-state relay concept (Instruments, 2006)
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There are many advantages of using solid-state relays as switches. They do not have mechanical contact so no physical wear out. Electromechanical relays have mechanical contacts so by the time with several time of on/off connections the relay will unusable. That problem is no longer there in solid-state relays (Solid-state Relays application guide, 2002).
Figure 39 A solid-state relay
Solid-state relays have high switching speeds and high frequency on/off operations. Therefore, they are suitable to use with inverters etc. Solid-state relays do not have contact failures also. Noises generated by solid-state relays are limited thus; they no longer have arc noises and the other noises are limited (Instruments, 2006), (Solid-state Relays application guide, 2002). There are some drawbacks in solid-state relay devices. The LED of the relay has a voltage drop so for smaller voltages the contact resistance (impedance) is high so solid-state relay will use some current for low voltages. When we consider the price of solid-state relay typically, the price is high but smaller relays the price is not an effect (Instruments, 2006), (Solid-state Relays application guide, 2002). Solid-state relay can handle on/off frequency up to 100 Hz for Dc load and 10 Hz on/off frequency for an AC load. So, for higher frequencies such as 1 kHz cannot be handle by using a solid-state relay (Solid-state Relays application guide, 2002).
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Figure 40 Solid-state relay inside mechanism (Solid-state Relays application guide, 2002)
2.7.1.2 Metal-Oxide Semiconductor Field-Effect Transistor (MOSFET) MOSEFT is a transistor device. It is a field-effect transistor. MOSFET’s are more sensitive than the FET’s and it is suitable for power applications (GPH, 2014). When compared to the other available switches field-effect transistor switches are the fastest (Instruments, 2006). MOSFET’s have a gate, drain and source terminals for its operations. Gate is the main operating terminal. When consider the other transistors metal-oxide field-effect transistor’s gate leakage is very small. The reason is input impedance of MOSFET’s are very high (GPH, 2014), (York, 2010). Source and drain are PN junctions. They supply the needed holes and electrons for the transistor operation. In the gate at the silicon surface, an oxide layer is grown and after that, a layer of polycrystalline silicon placed. The gate oxide layer of a MOSEFT is shown in the figure ## (6 MOS transistor, 2009).
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Figure 41 MOSFET construction (York, 2010)
Figure 42 Gate oxide layer (6 MOS transistor, 2009)
There are two types of MOSFET’s. They can be categories as N-channel and P-channel. N-channel MOSFET’s are formed by doping the source and the drain as electron rich (Ntype). P-channel MOSFET’s are doped by p-type as holes rich (6 MOS transistor, 2009).
Figure 43 N and P channel MOSFET symbols
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MOSFET’s fail due to several reasons. MOSFET’s cannot resists to high voltages than its voltage limit. A little exceed of voltage may fail the device. If a suitable heat sink is not attached to the MOSFET, for high rated currents they can fail due to temperature rise. The gate voltage has a range in MOSFET’s and the input voltage should be within that range if not the MOSFET will dissipate a considerable amount of heat (GPH, 2014). So to get the maximum power consumption by the MOSFET required gate voltage must be supplied.
Figure 44 A MOSFET
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2.7.2 State of Charge (SOC) Estimation Electric vehicle batteries are the most important device in electric vehicles. Battery performance and the battery safety are main parameters in electric vehicle and those should carefully analyze. In electric vehicles, customer safety is required most (Yuan, Wu, and Yin, 2013). Battery performance is generally rely on the chemical reactions happen inside the battery (Cheng et al., 2011). Volatility, flammability and entropy changes cause the batteries to ignite or explode. They can cause dangerous accidents and it could cause to decrease in demand of electric vehicle among the society (Yuan, Wu, and Yin, 2013). So the batteries must protect by extreme temperature, high charging and discharging rates and over or under voltages to maximize the battery safety and the performance (Cheng et al., 2011), (Densmore and Hanif, 2004). A small change in those parameters especially the voltage could reduce the battery health (Densmore and Hanif, 2004). Battery management system has an enormous opportunity in cell protection and the system safety. To improve the battery performance, safety and reliability on the battery management systems need an accurate parameter to control the cell balancing and protection systems. Sate of Charge is the parameter used by the battery management system to control its sub systems (Yuan, Wu, and Yin, 2013). State of Charge expressed as SOC can define as the available or the existing capacity of the battery as a percentage of the real or the rated capacity of the battery (Pattipati, Sankavaram, and Pattipati, 2011), (Cheng et al., 2011).
State of Charge provide a vast support to the battery management system to estimate the current status of the battery and help batteries to operate in its safe range by controlling the charging and discharging. State of charge enhance the battery life and gives controlling signals to balance batteries (Cheng et al., 2011). Moreover, state of charge help to estimate the remaining battery use time and the range that can be travelled by the available battery power (Juang et al., 2015).
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State of Charge cannot be measured directly. It can only be estimated (Cheng et al., 2011), (Juang et al., 2015). There are various method of estimating State of Charge. Every method has its own advantages and disadvantages. Battery temperature, varying power request and the aging effect are the main challenges in accurate estimation state of charge (Yuan, Wu, and Yin, 2013). So to accurate State of Charge estimation required measurements of battery voltage, charging or discharging current and the battery temperature (Cheng et al., 2011). Battery damage, battery rapid aging, over charging and over discharging of batteries can minimized by State of Charge accurate estimation (Cheng et al., 2011). According to the (Yuan, Wu, and Yin, 2013) State of Charge estimation can divide into two groups as open-loop models and close-loop models. There are various state of charge estimation methods. Following list shows the most popular state of charge estimation methods used in electric cars. 1. Coulomb counting SOC estimation method 2. Fuzzy logic SOC estimation method 3. Impedance spectroscopy SOC estimation method 4. Kalman filtering SOC estimation method 5. Open circuit voltage SOC estimation method
Coulomb counting method is the most used method in battery state of charge estimating. It is first used in lead-acid batteries. That charge estimation method is known as “Peukert’s Law” (Juang et al., 2015). In this method, batter’s initial charge has to be known for charging and when discharging total battery charge has to be known. Charge is estimated in coulombs (Juang et al., 2015). To estimation of the charge a battery model has to be made. That battery model has variables such as temperature, current dynamics and aging. Fuzzy logic estimation method used logic based system structure to estimate the State of charge. In the article (Singh et al., 1999) the authors proposed a State of Charge estimation methods using fuzzy logic method with combination of coulomb counting and impedance spectroscopy separately. Digital electronics are most important in fuzzy logic method because it needs digital hardware.
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Another method for State of Charge estimation is impedance spectroscopy method. This method is used mostly to estimate lead acid battery charge in the automotive industry. However, this method is now used in electric vehicle technology. For estimate state of charge impedance based method cell resistance is taken as the main parameter (Juang et al., 2015). Impedance spectroscopy method needs a battery model to do its estimation task. A sample electromechanical impedance spectroscopy based battery model is developed in (Zhu et al., 2015) article. Impedance spectroscopy is offline method and it is cost effective (Qahouq, 2016). Typically impedance spectroscopy state of charge measurement is done by injecting a small ac signal into the battery and then analyzing the response. In (Qahouq, 2016) the author proposed a DC/DC converter based impedance spectroscopy strategy that can be operated without injecting ac signals into the battery. The specialty is that is an online method and it fast the estimation. Kalman filtering method is a online State of Charge estimation method and a closed loop battery model should develop to use this method to estimate state of charge. State of charge value is determine by the voltage error between the estimated voltage from the battery model and the measured voltage value. When the closed loop system is stabilized, the system will provide a voltage reading almost identical to the battery terminal voltage. This method is most relevant so it provide precise safety information about the battery. However this system is complex. Needs a accurate battery model and the computation is also complex (Yuan, Wu, and Yin, 2013).
Figure 45 Closed loop kalman filtered battery model (Yuan, Wu, and Yin, 2013).
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2.7.2.1 Open Circuit Voltage State-of-Charge Estimation Open circuit voltage based state of charge estimating technic is the easiest way to estimate the battery capacitance. Open circuit voltage method does not has complex computations and it is a cost effective method. Anyhow open circuit voltage based state of charge estimation need accurate charging and discharging voltages of the battery with respect to the state of charge. Each battery has a datasheet. These data is available in the data sheet. If the state of charge is computed based a cell model, it will produce much accurate state of charge values. Battery capacity varies with the time. Therefore, by the lifetime, accuracy of the open circuit voltage based SOC estimation reduced. So need to add the aging parameter to the battery model. Batteries have different voltages in charging and discharging. So when designing the cell balancing system we have to consider the both cell voltage profiles charging and discharging. The following figure shows how the battery terminal voltages varying with charging and discharging.
Figure 46 Battery Cell voltage and SOC variation during charging & discharging (Lu et al., 2013)
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Batteries are charged at all times in a given charging rate. Therefore in each time, charging voltage is as same as the previous reading. However, when considering the discharging factor of electric vehicles, discharging battery power is changeable so the discharge rate vary every time. When accelerating, electric vehicles are drained a large amount of power from the battery with a higher discharge rate. Therefore, the discharging voltage also will not remain the same. So the energy requirement when accelerating the electric car has to be accounted in the open circuit voltage SOC estimation method.
2.7.3 State of Health Estimation (SOH) State of health measurement is a required factor in electric vehicles. It predicts the battery condition respective to a newly manufactured battery (Micea et al., 2011). Moreover, it gives information about the available discharge capacity with its lifetime (Nejad, Gladwin, and Stone, 2010). Capacity degradation is a major problem in electric vehicle. So to determine the available life of the battery pack relevant state of health prediction is needed. With the life time of the battery when charging and discharging several times chemical reactions happen. Every time the battery is charged conversion of electrical energy to chemical energy occurs inside the battery. Likewise in discharging stored chemical energy covert into electrical energy by a chemical reaction. When those reactions happen several years, a chemical layer formed around the negative battery electrode. This layer called as the solid electrolyte interphase (SEI) and it increase the battery resistance and reduce the battery storage capacity (Nejad, Gladwin, and Stone, 2010). State of Health estimation required in electric vehicles for various task. There are hundreds of battery cells in an electric vehicle battery. Every battery has a different life cycle even they are manufacture in same time. Therefore, some cells may end their lifetime early. Then, to determine cells that close to failure required state of charge estimation. Safety of an electric vehicle is more important so that predict the end of life of the battery pack is done by using State of Health estimation.
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Battery capacity drops with the aging of the battery. Therefore when estimation of State of Charge there will be errors with battery agimg. Therefore, by adding a State of Health parameter to State of Charge estimation system will generate accurate State of Charge estimations over the lifetime of the battery stack (Nejad, Gladwin, and Stone, 2010). There are many different State of Health estimation methods available. Nevertheless, every method have different advantage and disadvantages (Nejad, Gladwin, and Stone, 2010). Different State of health estimation systems uses different internal battery parameters such as AC and DC impedance, charge and discharge current, battery terminal voltage, battery temperature, State of Charge and battery cycle numbers (Nejad, Gladwin, and Stone, 2010), (Micea et al., 2011). State of charge estimation process is complex. In (Micea et al., 2011) have mentioned two state of charge estimation methods; time window algorithm and history based state of health measuring technique. In window algorithm method, state of charge is calculated based on the recorded cycle capacitor drop. In the history based method state of charge estimation, predict according to the previously recorded battery state of charge values.
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2.8 Li-ion Battery Charging, Discharging and System Safety 2.8.1 CVL & DVL of a Battery Electric vehicles rely on the battery energy. That is why electric vehicle needs a battery management system to control its battery power. Protection of vehicle battery is a main prospect in electric vehicles. Every battery has a safe operation voltage range. Battery should be charged and discharge in this range to avoid damages to the battery. Therefore a battery has a charging voltage limit (CVL) and a discharging voltage limit (DVL) (Piao et al., 2015), (Einhorn, Roessler, and Fleig, 2011). If, a cell in the serially connected battery stack reaches to charging voltage limit or discharging voltage limit charging process or the discharging process has to be stopped without damaging the cell. When designing the battery management system that should be accounted in the design.
Figure 47 CVL and DVL range of a battery (Einhorn, Roessler, and Fleig, 2011)
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2.8.2 Battery Discharging Process Battery discharge monitoring is essential in electric vehicles because to estimate the available battery capacity and to evaluate the available battery range. In battery discharge monitoring, two types of measurements are taken. One is about the energy characteristics of the battery and the other one is voltage-dropping characteristics (He, Peng, and Sun, 2004). Battery discharging current changes according to the vehicle driving condition, environmental temperature change and to the produced battery heat (He, Peng, and Sun, 2004). Large discharging currents reduce the battery lifetime so in batteries there is a maximum charging limit. In addition, batteries have a working temperature range and it is calculated based on the cell chemistry. To estimate the available battery capacity, an energy-dropping factor is calculated. The power dropping factor can be calculated by above equation (He, Peng, and Sun, 2004). 𝑇
∫ 𝑢. 𝑖𝑑𝑡 𝜁(𝐸) = 0 𝐸𝑛 Where, En – battery nominal energy (Wh), u – battery working voltage (V), i – battery working current (A)
Like the above equation a battery capacity dropping factor can be calculated as follows (He, Peng, and Sun, 2004). 𝑇
∫ 𝑖𝑑𝑡 𝜁(𝐶) = 0 𝐶𝑛 Where, Cn – battery nominal capacity (Ah), i – battery working current (A)
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When consider the voltage dropping characteristics, battery balancing is done by using the help of that evaluation. And the balancing current is determine by comparing those rates in each battery. The voltage-dropping factor can calculate as follows (He, Peng, and Sun, 2004). 𝑑𝑢 𝑟𝑣 = − 𝑑𝑡 𝑈𝑛 Where, Un – battery nominal voltage (V), rv – battery working current (V.h-1), u – battery working voltage (V)
Figure 48 Battery voltage diagram to different discharging capacities Appendix 05
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2.8.3 Battery Charging Process There are many charging method available in Li-ion battery charging. The most common method is constant current charging. Datasheet of a battery provide information about the maximum charging current. Battery charging voltage of a battery is much higher than the discharging voltage at same state of charge. That because when charging a battery internal resistance drops some amount of voltage. So to overcome this problem charging voltage is supplied to the battery much higher than the discharging. Typically, Li-ion battery is charges in constant current and when the constant current cutoff voltage is reached battery charge under constant voltage until the maximum charged. When constant current charging the voltage of the battery is rise and when shift to constant voltage the charging current is reduce dramatically. The maximum charge is identified by a minimum current value.
Figure 49 Charging characteristics of Panasonic NCR18650A Li-ion battery Appendix 01
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There are some different charging methods available for Li-ion batteries. Fast charging is a one of them. Not every Li-ion battery can fast charge. Fast charging is capable in high power Li-ion batteries such as Valance high current IFR26650PC battery (Appendix 04), A123 system’s high current ANR26650m1-B battery (Appendix 05). In fast charging, a battery is charged up to 80% of its SOC value by a constant high current rate. Then the remaining 20% amount is charged in constant voltage. In electric vehicles, a charging management unit is installed. The system is called smart charge system. In smart charge system user can schedule charges. The charging management system compute the available battery charge and it monitored the vehicle past driving cycles. Then a calculated charging pattern is made by the system with the consideration of the user’s choice. A smart charge charging management system is described in (Ishida, 2011).
Figure 50 Smart charging process of electric vehicles (Ishida, 2011)
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In (Becker, Schaeper, and Sauer, 2012) a time controlled charging pattern is described. The charging time is estimated by communication between the battery management system and the energy management system. Energy management system request a time prediction from the battery management system that how much charging time is needed by monitoring each battery. In here, the user’s opinion is not accounted. Energy management system calculate the charging time according to the battery management system’s response. The following figure shows the process of the time controlled charging pattern.
Figure 51 Time controlling charging pattern (Becker, Schaeper, and Sauer, 2012)
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2.8.4 High Voltage System Safety In electric vehicles, high current and high voltage is a common factor. Their voltage levels are higher than the safe voltage ranges and the also the electric system impedance is small (Zhao et al., 2016). Opiating current of electric vehicles can reached to 300A. Such current is more dangerous to a human body. If such an electrical system short the shorting current is pretty much higher than the maximum operating current (Zhao et al., 2016). So high voltage system design has to be done with a more consideration of the high voltage system and the passenger safety (Zhao et al., 2016). To avoid high voltage electric shocks to a passenger need a proper isolation between the vehicle chassis and the high voltage and low voltage electrical systems. There should be a 100 ohm per 1 volt isolation resistance in a DC circuit according to ISO6469-3 and 500 ohm per volt in AC (Kota and Balasubramanian, 2013). High voltage system monitoring include isolation condition monitoring of circuits, electrical system connection condition and high voltage connection condition etc. (Kota and Balasubramanian, 2013). Typical values on a protection circuit according to (Cao and Emadi, 2011) as follows.
Typical Programmable
Protection Item
Range
Overcharging detection voltage
3.9 – 4.4 V
Overcharging release voltage
3.8 – 4.4 V
Over discharging detection voltage
2.0 – 3.0 V
Over discharging release voltage
2.0 – 3.4 V
Discharging overcurrent detection voltage
0.05 – 0.3 V
Load short-circuit detection voltage
0.5V fixed
Charge overcurrent detection voltage
-0.1V fixed
Table 05 Typical programing values of protection circuit (Cao and Emadi, 2011)
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Between high voltage system and low voltage systems isolation amplifiers or optocouplers are installed to ensure the system safety. The auxiliary battery powers the battery management circuits. Therefore, the system circuit ground and the battery ground is different. Therefore high current needs to sense. So isolation amplifiers are disconnected by photoMOS relay when voltage sensing is not done. The following figure shows the isolated cell balancing system of Toyota Prius 2009 version.
Figure 52 Typical Isolated BMS in electric vehicles (Cao and Emadi, 2011)
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Moreover, the electric vehicle safety system should include high voltage safety features for connector opening, cover open and for a vehicle crash situation. High voltage interlocks are installed in electric car to cut of the high voltage battery from the system when if a safety issue happen. A typical high voltage interlock system is shown in the above figure.
Figure 53 High Voltage Interlock system (Kota and Balasubramanian, 2013)
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System Analysis
Chapter 03
System Analysis
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3.0 Project Analysis 3.1 Electric Vehicle Battery Type Selection In electric vehicles, main power source is the battery system. Therefore electric vehicle batteries need more attention. Battery safety is more important. The distance can be travelled by electric cars are lower than the normal combustion vehicles. So to improve the travelling distance, electric vehicle batteries should be able to store considerable amount of power. Electric vehicle batteries need high energy density and the self-discharge rate should be smaller. Moreover the single-cell voltage also effect on the performance of the battery stack (Kim, Kim, and Moon, 2012). In the literature review I have discussed about three main battery types that can use for electric vehicles (Li-ion, Ni-MH & Fuel cell). From them fuel cell battery technology is still developing and in the future there will be excellent fuel cell batteries. Lead-acid batteries are the traditional batteries used in combustion vehicle for decades. Although the lead-acid battery, is not suitable for the electric vehicles power applications. The reason is that the lead-acid battery’s energy and the power densities are lower than the other available batteries. With referring to the Table-01 lead-acid battery is the battery that have the lowest energy density and the power density when considering batteries. So lead-acid is not suitable for the electric vehicle applications. Nevertheless, lead-acid batteries can use for the experimental purposes in the electric vehicle. Li-Po battery has the highest power density than the other available batteries. Anyway Li-Po batteries are not suitable for the electric vehicle applications because of the safety reasons. Li-Po batteries are dangerous, hence with a collision they can explode. Over charging a Li-Po battery may cause a huge fire. Passenger safety is more important in electric vehicles so Li-Po is not a suitable battery for electric vehicles. As describe in the literature review hybrid electric vehicle and electric vehicle manufactures use two type of batteries to power there vehicles. Ni-MH and Li-ion are the two main battery type that the vehicle manufactures use. In hybrid electric vehicles NiMH batteries are used as the secondary power source (Kulkarni, Kapoor, and Arora, 2015).
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NiMH batteries have higher power and energy density like as in the Li-ion batteries and from safety vice NiMH is better than the Li-ion battery. NiMH batteries are larger in volume and also heavier than the Li-ion battery. If we consider the weight and energy, volume and energy ratios of the NiMH and Li-ion batteries Li-ion have a ratio at least three times more than the NiMH battery (Dhameja and Dhameja, 2000). In electric vehicle application weight is also so important. Higher weight will reduce the battery energy so the electric vehicle weight must be reduced. NiMH batteries has a lower weight to power ratio than the Li-ion battery. When using same power Ni-MH has a higher weight than the Li-ion. So Ni-MH batteries are not appropriate for electric vehicle applications. Li-ion battery is using wildly in electric vehicle applications (Kim, Kim, and Moon, 2012), (Wang and Kao, 2014), (Kulkarni, Kapoor, and Arora, 2015). Li-ion battery has the second highest energy and power density. Moreover, Li-ion has the highest cycle life, good pulse power density and good temperature operation range. Therefore Li-ion is used more in electric vehicles by electric vehicle manufactures (Dhameja and Dhameja, 2000).
Figure 54 Power and Energy density comparison (Kawase and Maebara, 2011)
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3.2 Battery Management System Architecture Selection Battery management system architecture has a higher percentage of contribution to the whole cell balancing system performance. The structure of the battery management system has to design perfectly by analyzing the other sub systems.
Figure 55 Typical battery management system structure (Stuart et al., 2002)
As described in the literature review mainly there are two types of battery management systems. They are centralized battery management and distributive battery management syetms. Centralized structure cannot use for a large number of cells like in electric vehicles. The centralized system need a good processor that have good processing speed and a higher bit rate. That kind of processors or microcontroller are more expensive. There is a huge load of work on that single processor when operating. So the processor’s life time can be decreased. Therefore, centralized battery management system architectures are not much suitable for the electrical vehicle applications especially for a large amount of serially connected Li-ion cells. Because electric vehicles systems should have a high efficiency and a better life span. Distributed battery management system architectures have spread their control through their balancing system. In distributed battery management structure series connected battery cells are divided into several groups and they are balanced by separate controllers. ~ 71 ~
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Those controllers are communicating between them. If somehow that communication line broken the whole system will unbalanced and total system could be failed. So considering the drawbacks in those centralized and distributed battery management structures a combining battery management architecture was developed (figure 56). It is a combination of centralized and distributive structures. Distributive structure is used in cells and series connected cells are divided into several packs. Each and every pack has a separate controlling unit. That unit will measure cell voltages and balance required cells. Those controllers are not going to communicate between them like in distributive structure. Sub controller are controlled and balanced by a main controller. A centralized system is used to control the battery management system. Each cell pack are going to be controlled by using a main controller. Sub controllers are communicated using serial communication to increase the speed and accuracy. The combination of the centralized and distributive architectures will work perfectly.
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Battery pack
Battery pack
Battery pack
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Sub battery management controller
Sub battery management controller
Sub battery management controller
Figure 56 Battery management system architecture design
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Main battery management controller
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3.3 Cell Balancing Method Selection Cell balancing system is the core of the battery management system. All the other systems in the battery management system work directly for the cell balancing system. So the cell balancing method is selection is very important. In the literature review described main two balancing paths. They are active balancing and passive balancing. Passive balancing is not suitable for electric vehicles because excess energy of the cells are dissipated as heat by resisters. Electric vehicles main power source is batteries so if the battery energy is wasted the vehicle efficiency fall down. Therefore passive balancing methods are not suitable for the electric vehicle applications. Active balancing methods are suitable for electric vehicle applications. But not all methods in the active balancing are applicable for electric vehicle. So the most suitable method has to be selected. Active balancing cell balancing systems can divide into three methods they are capacitor based active balancing methods, Inductor or transformer based active balancing methods and energy converter based cell balancing methods. They have different characteristics. To select a good method all the active balancing systems have to compare. Main advantages and disadvantages of active balancing systems displayed in the table on next page. Active cell balancing methods Main advantages Main disadvantages Switched Controlling strategy is Equalization speed is low capacitor simple Required switches is high Both charging and discharging Capacitor based cell balancing methods
Single switched Simple control strategy capacitor Both for charging and discharging One capacitor is used Double tiered Balancing time has reduced switched than the switched capacitor capacitor method Both for charging and discharging
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Intelligent control needed Equalizing speed is not much high Required switches is high Equalization speed is not much high
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Modularized switched capacitor
Single inductor
A good method for large number of series connected cells. Both for charging and discharging Equalization is very good
Multi inductor
Equalization speed is very good Balancing efficiency is good Single winding Equalization speed is transformer Transformer magnetic loss is low
Inductor or transformer based cell Multi winding Equalization speed is good balancing transformer methods
Multiple transformer
Equalization speed is good New cells can be easily added to the system Equalization speed is good
Modularized switching transformer Cuk converter
Equalization efficiency is good Equalization speed is good Easy for design
Buck-boost converter Energy converter based cell balancing methods
Flyback converter Ramp converter Full-bridge converter Quasi-resonant converter
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Intelligent control is needed Equalization speed is not much high
Control structure is complex Need filtering capacitors Precise state of charge estimation needed Only suitable for charging Need filtering capacitors Implementation cost is high Control strategy is complex Even for an additional cell the whole system must be re-designed Implementation cost is high For an additional installation of cell the whole system has to be changed Has a complex control strategy Cost is high Controlling method is complex Controlling is complex High cost
Perfect state of charge estimation needed Implementation cost is high intelligent control strategy needed Good for large series Accurate state of charge connected cells estimation is needed Equalization speed is fine Complex control strategy Very good equalization Controlling of the system is speed complex Efficient cell balancing Implementation cost is high system Controlling method is Implementation simple complex Table 06
Cell balancing system comparison (Daowd et al., 2011)
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Different balancing method have different properties. So for my cell balancing system design I chose buck-boost converter method and the double tiered switched capacitor balancing method. The double tiered switched capacitor method is a development of the switched capacitor method. Balancing time of double tiered capacitor method has reduced than in the switched capacitor method and the single switched capacitor method. Implementation cost of this method is not much high. So I select this balancing method for one of my design. When consider the buck-boost balancing method its equalization speed is better than the capacitor method. But the implementation cost is high but not much. By using buck-boost method each cell can balance at the same time. So it is a good method. Usually both buck and boost methods are not used for a balancing system together. It is pointless because the energy loss is significant. For future work I’m going to develop the boost method because by boost method output balancing voltage can be increased than the battery voltage. So the excess charge will be able to transfer to the cell pack without using step up transformer. It is an energy conversion method so balancing efficiency is high. But a boost converter circuit has to build for every cell. For large number of cells the cost will be more. Also the circuit space could be large. Therefore this method must be developed to overcome these problems.
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3.4 Analysis of State of Charge Estimation State of charge is the parameter which states about the battery’s available capacity. Battery management system use state of charge to manage its controls such as battery balancing, discharging time estimation, charging time prediction, cell safety purposes etc. There are various ways of estimating the state of charge of a battery. In the literature review I have briefly explained about some of available state of charge measuring methods. A comparison based analysis need to select the best state of charge estimating technique. The following table is shown a comparison between State of Charge techniques I have mentioned in the literature review.
SOC estimation method Coulomb counting method
Advantage
Disadvantage
Implementation is easy
The initial battery SOC
If the current measurement value should be estimated is good will give accurate correctly SOC by this method
Not suitable for batteries that have varying dynamic conditions regular current measuring recalibration
points
a
needed Fuzzy logic method
A online SOC measuring At sometimes this method technique A
digital
is not accurate logic
analysis
based For large number of cells it is difficult to implement a fuzzy
logic based SOC
estimating system Impedance method
spectroscopy It can be used also for the A signal generator has to SOH estimation
build to inject ac signals to batteries High cost Sensitive to temperature
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Kalman filter method
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It is an accurate method Online
SOC
The
model
is
more
estimation complex and has to do
method
more computation
Noises
are
mostly The system gain should be
eliminated
always stable if not there could be errors
Open method
circuit
voltage It is an accurate method of Long resting time needed SOC estimation Implementation is easy It is a cost effective online SOC measuring method
Table 07 Comparison between SOC measuring methods (Pattipati, Sankavaram, and Pattipati, 2011), (Lu et al., 2013)
According to the above comparison Kalman filtering method is the best available accurate state of charge estimation method. But that method is hard to implement. A vast range of study has to be done to implement such a system. For my future implementation process I am looking forward to design a SOC system with kalman filtering technique. As my project I am going to implement a three cell sample battery cell balancing system. For that implementation I am going to use the open circuit voltage method for state of charge estimation. Open circuit voltage based state of charge estimation method is an accurate method. But with the time when charging and discharging battery temperature varies to for accurate estimation of SOC some resting time needed for this method. Every state of charge estimation methods are not suitable for every type of battery. Different types of batteries have different kind of battery chemistry. Also the measuring technic of various SOC estimating technics is different one method to another. Therefore every technic is not suitable for all types of batteries.
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The following table has shown applications of considered SOC method with the SOC estimating inputs.
SOC estimation method Coulomb counting method
Application
Sensing parameters and inputs
Available for all battery Current, types
Capacity,
Coulomb efficiency, Self-discharge rate Initial SOC values
Fuzzy logic method
Applicable for all types of Current batteries
Impedance
Voltage
spectroscopy Can use in any battery type Resistance
method Kalman filter method
For all battery types
Current, voltage, capacity Coulomb efficiency, Self-discharge rate Initial SOC value Battery model
Open method
circuit
voltage Lead-acid, Li-ion and ZnBr Voltage batteries
Rest time
Table 08 Applications and SOC measuring variables (Pattipati, Sankavaram, and Pattipati, 2011), (Lu et al., 2013)
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3.5 Cell Balancing Control by Open Circuit Voltage SOC Estimation 3.5.1 Designing Limitations of OCV Based SOC Estimation Open circuit voltage based state of charge estimation is one of the battery capacity measuring techniques that I mentioned in the literature review. Open circuit voltage and state of charge of the battery are not proportional. Relationship between the SOC and the OCV varies differently in different conditions. When charging and discharging battery has a different voltage ranges. Charging voltage is typically high than the discharging voltage. Therefor for same SOC value in charging and discharging will not get the same voltage. That is one variation. Temperature of the battery or the system also change the relationship between OCV and SOC. When the temperature changes, as described in the literature review battery chemical reaction speeds changes. So when temperature changes cell open circuit voltage is also changed (figure 57).
Figure 57 Cell voltage change according to different temperatures Appendix 03
Again when the battery gets old capacity of the battery cell voltage is drifted. In a battery there is a life cycle period. When available cycle life is reducing the internal battery resistances. So when charging or discharging a significant voltage drop might happen in older batteries. Therefor we can see that the battery life time also affect the relationship of OCV and SOC. ~ 80 ~
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Then comes the charging and discharging rate. When in higher charging and discharging rates battery get tempered. That will reduce the battery voltage due to rise of the temperature. So when estimating the SOC by OCV charging or discharging rate of the system need to be considered. The following figure (figure 58) shows cell voltage variation for different discharge rates.
Figure 58 Cell voltage change according to different discharging rates Appendix 03
I am going to build a sample system and the following conditions and limitations are applied in my real implementation. i.
The temperature effect on the SOC when measuring OCV is not considered in my design.
ii.
The implemented system is going to be charged in a constant current rate so the voltage difference will not much different.
iii.
When discharging the battery in several discharging rates, changes the OCV measurement. Therefore to reduce the discharging error of my SOC measurement I am going to limit the discharging rate to a certain value to do the implementation easily.
iv.
Cell aging or the State of Health of the battery is not considered.
v.
Both charging and discharging voltage ranges are going to accounted in my real implementation.
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3.5.2 Cell Balancing Technique As I mentioned in the literature review batteries have difference power storing capacities. When those batteries are connected in series when charging and discharging some batteries might get lower charge while others get higher charge. Battery balancing is there to distribute the charge fully within batteries to get the maximum effectiveness. I have selected two cell balancing methods to design my sample system. They are double tiered switched capacitor method and buck-boost balancing method. As I said before for my implementation I am going to use the tiered switched capacitor method. This method is described in the literature review. In this capacitor based cell balancing method excess energy of highest charged battery cell transferred to the lowest charged battery cell by operating a switching pattern. When the voltage gap between the cells increase the excess energy amount also increases. That means transferring energy of higher voltage difference is higher than the transferring energy of lower voltage difference. To determine the transferring energy some computation has to be done. The equation to determine the transferred energy can be implement as follows. First of all we have to determine the battery capacity change for 1V difference. For that we need the battery capacitance in mAh and the battery high and the low voltage limits. This equation is made for both charging and discharging.
If, 𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 − 𝑪𝒃𝒂𝒕
𝑚𝑖𝑛𝑖𝑚𝑢𝑚 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 − 𝑽𝒎𝒊𝒏
𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 − 𝑽𝒎𝒂𝒙
𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑓𝑜𝑟 1𝑉 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 =
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𝐶𝑏𝑎𝑡 (𝑚𝐴ℎ𝑉 −1 ) − (𝟑. 𝟏) 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛
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If the voltage difference of the two batteries are K the transferred power can be calculated as follows, 𝑇𝑟𝑎𝑛𝑠𝑓𝑒𝑟𝑟𝑒𝑑 𝑝𝑜𝑤𝑒𝑟 𝑓𝑜𝑟 𝑲 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 =
𝐶𝑏𝑎𝑡 × 𝐾(𝑚𝐴ℎ) (𝟑. 𝟐) 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛
Then the conversion of mAh to Wh can be done as follows, 𝐸(𝑊ℎ) = 𝑚𝐴ℎ ×
𝑣𝑜𝑙𝑡𝑎𝑔𝑒 1000
In here the voltage if the battery voltage gap K, 𝐸𝑛𝑒𝑔𝑦 𝑖𝑛 𝑊ℎ =
𝐶𝑏𝑎𝑡 𝐾 ×𝐾 × 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 1000
𝐶𝑏𝑎𝑡 𝐾2 (𝑊ℎ) − (𝟑. 𝟑) 𝐸𝑛𝑒𝑔𝑦 𝑖𝑛 𝑊ℎ = × 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 1000
Watt has to be converted into joule, 1 W is equal to 3600J 𝑇𝑟𝑎𝑛𝑠𝑓𝑒𝑟𝑟𝑒𝑑 𝑝𝑜𝑤𝑒𝑟 𝑖𝑛 𝑱 =
=
𝐶𝑏𝑎𝑡 𝐾2 × × 3600 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 1000
𝐶𝑏𝑎𝑡 × 𝐾 2 × 3.6 ( 𝐽 ) 𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛
So the transferred power can be calculated by the following equation. 𝑻𝒓𝒂𝒏𝒔𝒇𝒆𝒓𝒓𝒆𝒅 𝒑𝒐𝒘𝒆𝒓 (𝑱) =
𝑪𝒃𝒂𝒕 × 𝑲𝟐 × 𝟑. 𝟔 𝑽𝒎𝒂𝒙 − 𝑽𝒎𝒊𝒏
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− (𝟑. 𝟒)
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In double tiered switched capacitor method, the energy transferring between cells is done by using capacitors. In the above equation the maximum energy for a certain voltage gap is calculated. Anyway all the amount of energy cannot be transferred to the lower capacity cell in a one capacity charging or discharging cycle. Because if it has done, the balancing time might large and also the energy efficiency will be small. So the best method of discharging voltage energy is the pulse discharge method. Energy is transferred to the lower voltage battery by small energy packets from the maximum capacity cell. The maximum transferred energy of a pack is changed when the duty cycle of the supplied pulse signal changes. Energy stored in a capacitor for a certain duty cycle can calculate by the following process. Instant charged voltage of capacitor can calculate by following equation, 𝑡
𝑉𝑐ℎ𝑎𝑟𝑔𝑒 (𝑖𝑛𝑠𝑡𝑎𝑛𝑡 𝑐ℎ𝑎𝑟𝑔𝑒) = 𝑉𝑚𝑎𝑥 − (𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 )𝑒 − 𝑅𝐶 ;
Where, R is the circuit resistance, C is the capacitance and Vmin is the voltage of the lower charged cell and Vmax is the voltage of maximum charged cell. Following figure (figure 59) shows the capacitor charging and discharging cycles for the pulse signal in D1T and D2T charging and discharging duty cycles.
Figure 59 Pulse charging and discharging for D1T and D2T duty cycle (Daowd et al., 2013)
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When the frequency of the pulse signal is F then the time period of the signal can calculate as follows, 𝑇𝑖𝑚𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑖𝑔𝑛𝑎𝑙 =
1 𝐹
Duty cycle time is a percentage of the time period and the duty cycle percentage of the signal. Therefore duty cycle time can be calculated by following equation. 𝑖𝑓 𝑡ℎ𝑒 𝑑𝑢𝑡𝑦 𝑐𝑦𝑐𝑙𝑒 𝑝𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑖𝑠 𝑫𝑻𝑷% 1 × 𝐷𝑇𝑃% − 𝐹
𝐷𝑢𝑡𝑦 𝑐𝑦𝑐𝑙𝑒 𝑡𝑖𝑚𝑒 (𝐷𝑇) =
(𝟑. 𝟓)
Instantaneous charged voltage can compute by using the following equation, 𝑇
𝑉𝐶𝑇 = 𝑉𝑚𝑎𝑥 − (𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 )𝑒 − 𝑅𝐶 −
(𝟑. 𝟔)
Where, VCT is the charged voltage in any instantaneous time (v),
Capacitor charging or discharging current is another main factor that needs to evaluate the transferred power. In a capacitor if C is the capacitance of the capacitor, V is the voltage across the capacitor and if the current is I, the discharged or charged current I can calculate as follows, 𝐼=𝐶
𝑑𝑉 𝑑𝑥
V is the initial voltage in the capacitor. For an instant time, the instantaneous current IDT can calculate by substituting the VCT value to the above equation. 𝐼𝐶𝑇 = 𝐶
𝑑(𝑉𝐶𝑇 ) 𝑑𝑥 𝑇
𝐼𝐶𝑇
𝑑(𝑉𝑚𝑎𝑥 − (𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 )𝑒 − 𝑅𝐶 ) =𝐶 𝑑𝑥
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(𝟑. 𝟕)
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Power generation can calculate by the following typical equation, 𝑃 = 𝑉𝐼 (𝑊)
So the instantaneous transferred power can represent as follows, 𝑃𝐶𝑇 = 𝑉𝐶𝑇 × 𝐼𝐶𝑇 − (𝟑. 𝟖) 𝑇
𝑃𝐶𝑇 = [𝑉𝑚𝑎𝑥 − (𝑉𝑚𝑎𝑥 −
𝑇 𝑉𝑚𝑖𝑛 )𝑒 − 𝑅𝐶
𝑑 (𝑉𝑚𝑎𝑥 − (𝑉𝑚𝑎𝑥 − 𝑉𝑚𝑖𝑛 )𝑒 − 𝑅𝐶 ) ] × [𝐶 ] (𝑊) 𝑑𝑥
Power transferred in a one duty cycle can calculate by integrating PT from 0 to DT of time. So; 𝐷𝑇
𝐶ℎ𝑎𝑟𝑔𝑖𝑛𝑔 𝐸𝑛𝑒𝑟𝑔𝑦 𝑓𝑜𝑟 𝑎 𝑜𝑛𝑒 𝑑𝑢𝑡𝑦 𝑐𝑦𝑐𝑙𝑒 = ∫ 𝑃𝑇 𝑑𝑡 (𝑊𝑠) − (𝟑. 𝟗) 0
Where DT is the duty cycle time (Equation 3.5). Energy in joule for a one Wh of power is 3600. Energy for a 1Ws can calculate multiplying 3600 by 60*60(seconds for a one hour) =3600. So that means 1Ws is equal to 1J. Therefore, 𝐷𝑇
Pulse charge energy = ∫ 𝑃𝑇 𝑑𝑡 (𝐽) − (𝟑. 𝟏𝟎) 0
Likewise when discharging, values of equation 3.8 changes as follows, 𝑉𝑚𝑎𝑥 = 𝑉𝑚𝑖𝑛 𝑎𝑛𝑑 𝑉𝑚𝑖𝑛 = 𝑉𝑚𝑎𝑥 So, 𝑇
𝑃𝐷𝑇 = [𝑉𝑚𝑖𝑛 − (𝑉𝑚𝑖𝑛 −
𝑇 𝑉𝑚𝑎𝑥 )𝑒 − 𝑅𝐶
𝑑 (𝑉𝑚𝑖𝑛 − (𝑉𝑚𝑖𝑛 − 𝑉𝑚𝑎𝑥 )𝑒 − 𝑅𝐶 ) ] × [𝐶 ] (𝑊) 𝑑𝑥
− (𝟑. 𝟏𝟏) ~ 86 ~
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In battery balancing, energy is transferred from highest capacity cells to the lowest capacity cells in the battery stack. The following figure clearly describe how is the energy transferring process happens between cells (figure 60).
V2 3.2V
V2 2.6V
V3 3.15V
V3 2.86V
V4 3.11V
V4 2.73V
Figure 60 Transferring energy between cells
Above figure shows different sates of battery balancing. In my system always energy is transferred between all cells that have voltage gaps. Energy transferring current rate should smaller than maximum discharge of the battery. As well as the addition of the balancing current and the batter stack discharging current should be smaller than the available maximum discharge current of the battery. According to the equation 3.4 when the voltage gap between two cells increases the dischargeable energy also increase. Therefore, the balancing time will rise when the voltage gap increases. 𝑻𝒓𝒂𝒏𝒔𝒇𝒆𝒓𝒓𝒆𝒅 𝒑𝒐𝒘𝒆𝒓 (𝑱) =
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𝑪𝒃𝒂𝒕 × 𝑲𝟐 × 𝟑. 𝟔 𝑽𝒎𝒂𝒙 − 𝑽𝒎𝒊𝒏
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For a battery Vmax , Vmin and Cbat are constants. So the transferring energy is directly proportional to the squire of the voltage gap between two nearby cells. To reduce the balancing time we can adjust the discharging pulse frequency to a higher value to discharge fast. But in my sample implementation I am not going to use different frequencies for balance batteries. I am going to choose an optimum frequency for every considered voltage gaps. So in my sample system the balancing time will be high for larger voltage gaps. I will reduce the balancing time in future development of this system, to get maximum performance.
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Chapter 04
System Design
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System Design
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4.0 System Design 4.1 Li-ion Battery Selection Before design the battery cell monitoring and cell balancing system we should select the suitable battery we are going to use for our project. As describe in the literature review, and system analysis Li-ion is the most suitable battery for the electric vehicle applications. So we have selected the Li-ion battery by considering the special characteristics of its. There are four types of Li-ion cells described in the literature review. From that for most of the electric vehicle applications small cylindrical type Li-ion cells are used. So we have selected 3.7v Li-ion small cylindrical type cells to build our system. Li-ion cells are available in different capacity. The maximum capacity of Li-ion cells are around 3000mAh. So we are going to use a Li-ion battery cell a capacity of 3000mAh. So we selected three cell types. One is for, cell monitoring and balancing system sample and the other two are for the real implementation. From that two Li-ion batteries we are choosing finest battery for our use. We are planning to use Panasonic NCR18650A or UR18650ZTA Li-ion battery in actual making of the electric car. For testing purposes and sample implementation Panasonic CGR18650CG Li-ion battery is going to be use. Some specifications of the battery displayed bellow. Data sheets of NCR18650A, UR18650ZTA and CGR18650CG Li-ion batteries attached in Appendix 01, Appendix 02 & Appendix 03 respectively. Battery characteristics are more important when building battery management systems. To maximize the performance of the battery, to expand the life cycle of the battery and high safety of the battery can be only maintained by balancing the batteries known parameters. Whole cell monitoring and cell balancing system rely on the precise battery parameters. Some battery characteristics of the 3 battery types are displayed in the below table
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NCR18650A
UR18650ZTA
CGR18650CG
Nominal Voltage
3.6V
3.7V
3.6V
Typical capacity
3070mAh
3000mAh
2250mAh
Constant Current –
Constant Current –
Constant Current –
1475mA (Max)
1450mA (Max)
1500mA (Max)
Constant Voltage –
Constant Voltage –
Constant Voltage –
4.2V
4.35V
4.2V
Cutoff current –
Cutoff current –
Cutoff current –
59mA
58mA
110mA
(at 25oC)
(at 20oC)
(at 25oC)
Cutoff voltage –
Cutoff voltage –
Cutoff voltage –
2.5V
3.0V
2.5V
47.5g
49.0g
44g
Charging CC-CV
Discharging
Weight
Table 09 Li-ion battery characteristics Appendix 01, Appendix 02, Appendix 03
By looking at the volumetric density and gravimetric density of NCR18650A and UR18650ZTA we can determine that the NCR18650A Li-ion battery is better for the electric vehicle operation. Life cycle characteristic of the NCR18650A battery also better than the UR18650ZTA Li-ion battery. With 500 life cycle UR18650ZTA battery drops its capacity to below 2000mAh. However, in NCR18650A Li-ion battery after 500 life cycles its capacity drops only approximately 2300mAh. So NCR18650A battery has better characteristics than the UR1650ZTA battery.
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Anyhow the motor controlling engineer of our e-wolf team has selected a motor with a power of 20kW. According to the performance curve with to the input voltage the current increases. The current change between 0A and 270A range. But NCR18650A and UR1650ZTA as a single line series battery pack cannot handle a current like that. The maximum discharge rate of NCR18650A and UR1650ZTA is bellow than the above value. Datasheet of the electric motor attached in Appendix 08. If the NCR18650A and UR1650ZTA batteries discharge with a 2C rate (That is according to the datasheets of NCR18650A and UR1650ZTA about 6A of power). To supply a current of 270A the needed parallel connected cell amount is. 𝐶𝑒𝑙𝑙 𝑎𝑚𝑜𝑢𝑛𝑡 𝑛𝑒𝑒𝑑𝑒𝑑 𝑡𝑜 𝑐𝑜𝑛𝑛𝑒𝑐𝑡 𝑖𝑛 𝑝𝑎𝑟𝑎𝑙𝑙𝑒𝑙 =
270𝐴 = 45 𝑐𝑒𝑙𝑙𝑠 6𝐴
Therefore, to produce a high current to match the motor energy requirement for the maximum performance about 45 batteries have to connect parallel. The voltage of the motor is 96V and to match that voltage we have to connect Li-ion batteries in series. Even the motor voltage is 96V batteries should not have to the voltage limit. So the battery voltage must be some higher than the motor voltage. In full power mode according to the motor performance curve in Appendix 08 the motor required a voltage about 100V. Therefor the supply voltage should be at least 120V. A buck converter should use to step down the voltage to the required amount. The required series cell quantity to match the 120V can be calculated as follows. 𝑆𝑒𝑟𝑖𝑒𝑠 𝑐𝑜𝑛𝑛𝑒𝑐𝑡𝑒𝑑 𝑐𝑒𝑙𝑙 𝑞𝑢𝑒𝑛𝑡𝑖𝑡𝑦 =
120 𝑉 = 33.3 ≈ 34 𝑐𝑒𝑙𝑙𝑠 3.6𝑉
The cell amount is calculated for the NCR18650A Li-ion cell which has an operating voltage of 3.7V. The parallel cell amount can be reduced by using valence’s IRF26650PC Li-ion cell or A123system’s ANR26650m1-B Li-ion cell. Both are high power cells and has a maximum pulse current of 120A and 100A respectively. Datasheets of A123system’s ANR26650m1-B Li-ion cell or IRF26650PC Li-ion cell is attached in Appendix 06 and Appendix 07 respectively.
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Some main cell characteristics of A123system’s ANR26650m1-B Li-ion cell or IRF26650PC Li-ion cell displayed on the table below.
IRF26650PC
ANR26650m1-B
Nominal Voltage
3.2V
3.3V
Typical capacity
2500mAh
2500mAh
Charging CC-CV
Constant Current – 2.5A
Constant Current –
(Max continuous)
2.5A (Max)
Constant Voltage –
Constant Voltage –
3.65V
3.6V
Fast Charge Current –
Fast Charge Current –
10A
10A
Cutoff voltage – 2.0V
Cutoff voltage – 2.0V
Max continuous current –
Max continuous current
25A
– 50A
Max pulse current (10s)
Max pulse current (10s)
– 100A
– 120A
CC
Discharging
Table 10 Li-ion high power battery characteristics Appendix 06, Appendix 07
These batteries can use to supply high current by reducing the parallel cell quantity. Because of the high discharge and charging current these batteries are use full in electric vehicle operations. But the cell price is higher than the NCR18650A and UR18650ZTA Li-ion batteries.
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4.2 Battery Management Architecture Design Battery management system architecture selection is most important. In the literature review I have shown that there are two main battery management system architectures. In the project analysis part I have analyzed those architectures and I have shown that the combination of centralized and distributed architectures is better for the electric vehicle operations. As describe in the analysis series connected cells are divided into several cell packs and those back have an individual pack controller. Those packs are controlled by a master controller. The amount of cells in the cell pack depends on the using voltage monitoring IC and by using microcontroller. I have found two voltage monitoring IC manufactured by Texas Instrument and Linear technologies. Those ICs are not going to use for my prototype implementation. But for the future development of my system they are useful. Texas Instrument battery monitoring IC bq76PL536 is suitable for the electric and hybrid electric vehicle battery monitoring. It support for all battery types and 3 to 6 cells can connect to the battery monitoring IC. The data sheet of bq76PL536 is attached in Appendix 04. Linear Technology’s LTC6802-1 battery stack monitoring IC is suitable for Li-ion cells. Only Li-ion cells can connected to this IC. Up to 12 Li-ion cells can be monitored and connected to the LTC6802-1 IC. A sample battery management system module made by using LTC6802-1 is available in the article “A modularized charge equalizer using a battery monitoring IC for series-connected Li-ion battery strings in electric vehicles” (Kim, Kim, and Moon, 2013). The data sheet of LTC6802-1 is attached in Appendix 04.
According to the battery monitoring IC going to be used the cell limit of a pack will be decided. Each cell pack will have temperature sensors to measure the battery pack temperature. When temperature is rising a fan will operate and increase the fan speed to cool the battery stack.
The following figure shows the controlling system of the battery management system. The equalizer system is not shown in the below diagram. ~ 94 ~
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Temperature Sensing Unit
Sub battery stack controlling IC
Cell Voltage Measuring Unit
Main System controlling IC Temperature Sensing Unit
Sub battery stack controlling IC
Cell Voltage Measuring Unit
Figure 61 Battery management system architecture designing
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Battery management architecture is a combination of distributive and centralized structures. As mentioned in the system analysis sub-controllers manage the cell packs while those sub-controllers are managed by the main battery management controller. A three cell pack is formed to implement the sample battery management system. For that above system architecture is not going to be used because only three cells are going to be balanced. A model sub cell balancing system is going to implement. Temperature measuring system, cell monitoring system and the cell balancing system are made with a controlling IC. The battery management system structure of the three cell balancing system is displayed below.
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Current Sensing Module
6ET011
System Interface (LCD)
Temperature Sensing Modules
Sub battery stack controlling IC
Cell Voltage Measuring Module
Cell Balancing Module with Isolation
Main Control & Safety Solid State Relay Switch
Battery Cooling Module
Figure 62 Sample three cell battery management system architecture
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4.3 Cell Voltage Measuring System Design When charging and discharging cells have different terminal voltages. Again for various discharging rates cells get various terminal voltages. Most of the battery characteristics have some kind of relationship with the cell voltage. Therefore by measuring the cell voltage we can predict lot of battery information that needed in battery management systems. In my design I am going to estimate the state of charge by open circuit voltage method. Then the voltage measuring system should design minimizing errors. To measure the voltage of a circuit there are different methods used. The primary method is voltage dividing method. V1 12V
V: 1.09 V V(p-p): 0 V V(rms): 0 V V(dc): 1.09 V V(f req): --
V1 30V
R2 10kΩ V
V: 2.73 V V(p-p): 0 V V(rms): 0 V V(dc): 2.73 V V(f req): --
PR1
R1 1kΩ
Analogue input Microcontroller
R2 10kΩ V
PR1
R1 1kΩ
Analogue input Microcontroller
Figure 63 Voltage divider based microcontroller voltage measuring Simulated by MULTISIM 2014
Above diagram shows the basic voltage dividing voltage measuring circuit. In the first picture a 12V battery is connected to the divider and that time the microcontroller input voltage is 1.09V. In the second picture a 30V battery is connected and the microcontroller input voltage is 2.73V. The voltage signal is given to analog pins of the microcontroller. In lot of microcontrollers the maximum analogue input voltage is 5V. So a voltage divider is needed. When coding the analogue read signal is multiplied by a constant.
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By doing some basic math’s we can find the real voltage of that system. For an example consider a cell with a voltage of “X” and the microcontroller input voltage is VPR1, 𝑉 − 𝑉𝑃𝑅1 𝑉𝑃𝑅1 = 10 𝑘Ω 1 𝑘Ω 𝑉 − 𝑉𝑃𝑅1 = 10𝑉𝑃𝑅1 𝑆𝑜; 𝑉 = 11𝑉𝑃𝑅1 In the code the VPR1 reading has to multiply with 11 to get the real voltage reading. But in my system there are three batteries connected in series. There are different voltages in different levels. So voltage dividing method is not going to help and need extra coding to determine a cell’s voltage. Also in my system considerable current passes through battery when charging and discharging. Voltage dividing circuit is using some current because of resisters. Microcontrollers are more sensitive to currents and the device could damage by a high current. So voltage dividing method is not suitable for my application. I am going to build a battery management system prototype for an electric car. Usually electric cars passes more than 200A when operating through batteries. So my voltage sensor should resistive to that amount of current without damaging the microcontroller. The design of the voltage sensor is based on op-amps. A comparator based op-amp model is developed as the voltage sensor. Some researchers are also used this type of voltage measuring units (Daowd et al., 2013). Sensing circuit has two input terminals and those have to connect to the battery. There is a one output terminal and a low pass filter is placed to reduce the current bouncing effects and other noises. In my simulation circuit I have used OPA4277PA operational amplifier and it has a typical operating voltage of ±20𝑉. I am supplying ±15𝑉 as the operating voltage of the amplifier IC. Sensors output terminal is giving cell voltage difference when the cell connected in series. Therefore additional coding is not needed. Normally microcontroller’s maximum input voltage is 5V. But in this voltage sensor gives voltage reading up to the cell’s maximum voltage value is smaller than 5V. It is around 4.3V and occurs when charging (Appendix 03).
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The sensor circuit is analyzed below. R3
R1
- Vb
10kΩ
10kΩ
+ Vb
1 2
B R5 10kΩ
-15V
U1A
3
11
R2
A
10kΩ
4
+15V
Micro controller Analogue Input
OPA4277PA
-15V
+15V V3
V2
15V
15V
Figure 64 Op-amp comparator based voltage sensor Drawn by MULTISIM 2014
‘A’ and ‘B’ are selected nodes of the circuit. Vb- is the low voltage terminal of the cell and the Vb+ is the higest voltage terminal of the cell. By appliying KCL for ‘A’ node, 𝑉𝑜𝑢𝑡 − 𝑉𝐴 𝑉𝐴 − 𝑉𝑏− = ; 𝑅 𝑖𝑠 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑎 𝑟𝑒𝑠𝑖𝑡𝑒𝑟 𝑅 𝑅 𝑉𝑏− = 2 ∗ 𝑉𝐴 − 𝑉𝑜𝑢𝑡
− − − − − −(1)
In a op-amp resistance betwwen the input terminal in the above diagram between A and B are very large. So there is no current flow between A and B nodes through the op-amp. Therefore voltages on the A and B point are same. So, 𝑉𝐴 = 𝑉𝐵 . By applying KCL for node ‘B’, 𝑉𝑏+ − 𝑉𝐵 𝑉𝐵 − 0 = 𝑅 𝑅 𝑉𝑏+ = 2 ∗ 𝑉𝐵 − − − − − (2)
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By using equation (1) and (2), 𝑉𝑏− = 2 ∗ 𝑉𝐵 − 𝑉𝑜𝑢𝑡 𝑉𝑏− = 𝑉𝑏+ − 𝑉𝑜𝑢𝑡 𝑉𝑜𝑢𝑡 = 𝑉𝑏+ − 𝑉𝑏− But, 𝑉𝑏𝑎𝑡 = 𝑉𝑏+ − 𝑉𝑏−
; 𝑡ℎ𝑒 𝑏𝑎𝑡𝑒𝑟𝑦 𝑣𝑜𝑙𝑡𝑎𝑔𝑒
So, 𝑉𝑏𝑎𝑡𝑡𝑒𝑟𝑦 = 𝑉𝑜𝑢𝑡 = 𝑉𝑏+ − 𝑉𝑏− To limit the bounsing effects and unwanted noices two capacitors are placed in parallel to the Vb+ terminal. When working with op-amps, high frequency noise signal could be generated. So a low pass filter is placed at the output terminal to cut the un-wanted noises. In the circuit the current passes through the PR1 is so small so better to use with microcontrollers for higher currents. R3 +15V
Battery Terminal Input V1 3.7V R2 Battery Terminal Input +
U1A
10kΩ
C1 100nF
A PR1
3 1 PR2
2
11
10kΩ C2 100nF
10kΩ
4
R1
I: -185 uA I(p-p): 0 A I(rms): 185 uA I(dc): -185 uA I(freq): --
R5 10kΩ
OPA4277PA
-15V
-15V
+15V V3
V2
15V
15V
Figure 65 Voltage sensor simulation Drawn and simulated by MULTISIM 2014
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V
R4 1kΩ C3 100nF
Micro controller Analogue Input
V: 3.70 V V(p-p): 986 pV V(rms): 3.70 V V(dc): 3.70 V V(freq): 50.1 kHz
Individual Project
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The following figure shows how the voltage sensors are connected to the serially connected battery stack. I have used OPA4277PA op-amp for simulation purpose and for my system implementation I am going to use OPA277PA single op-amp IC (Appendix 09). -15V
+15V V3
V2
15V
15V
R3 +15V
R2
3
10kΩ
10kΩ C2 100nF
Micro controller Analogue Input 01
1 2
11
V1 3.7V
U1A
4
R1
10kΩ
C1 100nF
R5 10kΩ
OPA4277PA
-15V
R4 1kΩ C3 100nF
R8 +15V
10kΩ
V4 3.7V
R7
3
10kΩ
Micro controller Analogue Input 02
1 2
11
10kΩ C5 100nF
U2A
4
R6
C4 100nF
R10 10kΩ
OPA4277PA
-15V
R9 1kΩ C6 100nF
R13
V5 3.7V +15V
R12
3
10kΩ
C7 100nF
Micro controller Analogue Input 03
1 2
11
10kΩ C8 100nF
U3A
4
R11
10kΩ
R15 10kΩ
OPA4277PA
-15V
Figure 66 Voltage sensing system in the battery module Drawn by MULTISIM 2014
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System Design
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4.4 Current Sensing System Design Current sensing system in an electric car does a various task including involving in the available battery charge and the available battery power time and also in the State of charge estimation. Electric cars uses current in different quantities in different conditions. When accelerating motor use considerable current. At the maximum output power of the motor it uses about 300A of current. With the varying current, available battery time also varied according to the variation. So current measuring is needed. In electric vehicles different current sensors has to be used because of the high load of current. As well as for the battery safety the measuring sensors should give accurate reading. There are various methods for measure the current flowing through a cable or a wire. Hall-effect method is a one of the most used method for sense current. In high power applications hall-effect sensing is so effective. But has drawbacks also. Hall-effect sensor sense current to the change of the magnetic flux when changing the current flow. In my sample model I do not need a high current measurable current sensor because the maximum current of my model will be less than 15A. I am going to use Panasonic CGR8650CG Li-ion battery for my implementation. Batteries are arranged as two batteries are parallel and three packs of those parallel cells connected in series. Panasonic CGR8650CG Li-ion battery has a maximum capacity of 2,250mAh (Appendix 03). I have two batteries parallel so in my system I have 4500mAh of power. If the discharge rate of the system is 2C the maximum discharge current can be calculated as follows. 𝐹𝑜𝑟 1𝐶 𝑟𝑎𝑡𝑒 𝑡ℎ𝑒 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 = 4500𝑚𝐴ℎ ∗ 1𝐶 = 4500𝑚𝐴 𝐹𝑜𝑟 2𝐶 𝑟𝑎𝑡𝑒 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 = 4500𝑚𝐴ℎ ∗ 2𝐶 = 9000𝑚𝐴 Therefore the maximum current passes through my sensor will be always less than 15A. So have to use a hall-effect sensor that can be capable of handling 15A of current.
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As described in the (Yarborough, 2007) there are three types of current sensing methods are available. For my application I selected ACS712 current sensing IC. This sensor uses the Hall Effect method to sense current. This sensor is available in three different measuring current capabilities. It has 5A, 20A and 30A IC’s. I selected 20A ACS712 current sensor for the implementation (Appendix 10).
Figure 67 Current sensing IC ACS 712 Appendix 10
ACS 712 sensor is available as a sensor module also. There is no lot more difference between the sensor and sensor module but the sensor module is easy to use.
Figure 68 Current sensor module ACS 712
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ACS 712 hall-effect sensor has four input terminals that is connecting to the current source. Apart of that sensor has a supply voltage input pin, sensor out pin and the ground. The supply voltage of the ACS 712 sensor is typically 5V but the maximum value that can be supplied to the sensor is 8V. With the optimize range of the IC the sensitivity of the sensor varies. Typically 20A current sensor has a sensitivity value of 100mV/A. This value is very useful when coding to obtain the analogue value. Sensor is supply a voltage signal to the microcontroller when the current passes. The output of the sensor is connected to an analogue pin. The maximum reading of any analogue pin is 5V. Therefore some computation has to be done in the code to obtain the current value. Analogue pin reading
0
+5V
Digital value
0
1023
𝑉𝑜𝑙𝑡 𝑝𝑒𝑟 1 𝑏𝑖𝑡 =
5𝑉 1023
But the current sensitivity of the 20A sensor is100𝑚𝑉/𝐴. That states voltage change for 1 ampere is 100mV. So ampere change for 5V can be calculated as follows. 𝐴𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑎𝑚𝑝𝑒𝑟𝑒 𝑓𝑜𝑟 5𝑉 𝑐ℎ𝑎𝑛𝑔𝑒 =
5𝑉 × 1𝐴 = 50𝐴 0.1𝑉
Therefore the current change for 1 bit is, 𝐶𝑢𝑟𝑟𝑒𝑛𝑡 𝑐ℎ𝑎𝑛𝑔𝑒 𝑓𝑜𝑟 1 𝑏𝑖𝑡 =
50𝐴 1023
The analogue value can calculate as follows. 𝑉𝑎𝑙𝑢𝑒 =
𝐴𝑛𝑎𝑙𝑜𝑔𝑢𝑒 𝑟𝑒𝑎𝑑 𝑣𝑎𝑙𝑢𝑒 × 50𝐴 1023
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In arduino programming boards there is an analogue to digital converter and its bit amount is 10 bit. Some microcontrollers has ADC converters with different bit rates. When taking the analogue value in the code the computation part has to be done according to the available bit amount. Arduino has a 10 bit ADC so available digital values are equal to 210 = 1024 digital value patterns. If any other processor has an ADC bit value of 8 it has 28 = 256 digital value patterns. I am going to use arduino based control system for my implementation. When an analogue signal is given to an analogue pin of the arduino, the ADC converts the signal into digital and the digital values are lie between 0 and 1023. Arduino ADC has 1024 digital values. Always a digital value start with zero. So the values are lie between 0 and 1023. The following figure (figure 69) shows the ACS 712 sensor connections to the arduino. I have used atmega 2560 arduino mega processor to saw the sensor connections. The current sensor output is connected to an ADC port and for Vcc 5V power is given.
Figure 69 ACS 712 current sensor connections Drawn by using Proteus simulation software
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4.5 Temperature Sensing and Battery Cooling System Design Temperature is the most common factor that affects in every electric system. High temperature means low performance. So the temperature should be kept in an optimal range to avoid performance losses. Electric vehicles uses high amount of current each second. That means in every second some energy is converted to heat causes the temperature rise. Electric circuits generate some amount of heat due to resistances. That cannot be stopped but can be reduce. As mentioned in the above high temperature cause to low performance, also high temperature could damage electric circuits and other operating equipment. Especially in Li-ion batteries high temperature reduce the chemical reaction efficiency and could increase the internal impedance of the battery. It will affect the whole electric system and the electric car. Therefor temperature in an electric vehicle should be monitored and controlled. There are two temperatures that challenge the vehicle performance that is the environment temperature and the system temperature. Both are important should be controlled. There are countries that have various temperatures. Some have very high temperatures and some have very low. Because of seasonal changes temperature also change. Electric vehicles have a both cooling and a heating system for keep the temperature in right place. I am implementing a sample battery cell balancing system. For the temperature measuring and controlling system I am going to place a 12V dc fan to control the temperature. Temperature sensors are placed near batteries and the system circuits. Whenever a considerable temperature change detects, fan will increase the speed according to the temperature difference between a preset value and the measured value. I am not going to build the cooling system because for our country a cooling system is not needed. There are different electrical components in my system each and every component has different operating temperature ranges. So when controlling the system temperature, conditions of all components must be considered.
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The following table shows the operational temperature ranges of some components that I am using for my sample implementation. Component
Operational temperature range
ACS 712 20A sensor
-40 oC to 85 oC
6N135 optocoupler
-55 oC to 100 oC
Panasonic battery
Charging 0 oC to 45 oC Discharging -20 oC to 60 oC
TL082 operational amplifier
-40 oC to 85 oC
OPA277 operation amplifier
-40 oC to 85 oC Table 11
Operational temperature variation between electronic components Appendix 03, Appendix 09, Appendix 10
We can see that the optimum operational temperature ranges different in most components. Specially battery has different temperature conditions when charging and discharging and it is the lowest range. My system is a sample implementation and all the circuits including battery are stored together. So the operating temperature range of my system must be the temperature range of the battery. I divided the required temperature range of my system into several groups. Each group has different fan speed. The environmental temperature can be varying within 23 oC and 34 oC in over country. When the temperature difference between the electrical system of the car and the environment is large the produced heat by the car is dissipated without difficulty. But when the temperature difference is small the produced heat energy will be absorbed by the electrical system and the body of the car. So it will cause in car temperature rise. So it is recommended to adjust the fan speed control with the temperature difference of the car and the environment. But because of time limitation I am not going to use the difference to adjust the fan speed of my system.
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As I said before my system temperature range divide into several groups and the fan speed adjusted by the microcontroller by changing the duty cycle of the PWM signal supplied to the fan’s motor controller. For measure the temperature two temperature sensors are going to be use and they are placed near the battery and the circuit boards. LM35 temperature sensors are using for my implementation and the schematic diagram of the sensors are shown in the diagram (figure 70) below. The data sheet of LM35 temperature sensor is attached in Appendix 11. The LM35 temperature sensor has three pins to supply voltage, the ground and to the analogue output. The supply voltage of LM35 temperature sensor is in the range between -0.2V to 35V range. The out of the sensor is given as a voltage output and the maximum is output voltage is 6V. If in the operation LM35 measures up to its maximum temperature the sensor gain is varying a little than in the -40 oC to 125 oC. My system always will be in -40 oC to 85 oC temperature range so the sensor gain would be 9.8 (Appendix 11).
Figure 70 LM35 temperature sensors connections to the processor Drawn by using Proteus simulation software
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The temperature sensor gives and analogue voltage output and as in the current sensor design to get the actual value some computation has to be done. Temperature sensor is connected to an analogue pin and the maximum analogue pin reading is 5V. When converting to the digital value by 12 bit ADC convert in the atmega 2560 processor the maximum voltage reading will get a bit value of 1023 bits. So as done in the current sensor voltage reading per bit is, 𝑉𝑜𝑙𝑡 𝑝𝑒𝑟 1 𝑏𝑖𝑡 =
5𝑉 1023
Sensor has a gain of 9.8 mV/oC and the temperature reading for 5V can be calculated as follows, 𝑚𝑎𝑥𝑖𝑚𝑢𝑚 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑟𝑒𝑎𝑑𝑖𝑛𝑔 =
5000 𝑚𝑉 9.8 𝑚𝑉℃−1
= 510.2041 ℃
The temperature change for 1 bit is, 𝐶𝑢𝑟𝑟𝑒𝑛𝑡 𝑐ℎ𝑎𝑛𝑔𝑒 𝑓𝑜𝑟 1 𝑏𝑖𝑡 =
510.2041 ℃ = 0.4987 ℃ 𝑝𝑒𝑟 𝑏𝑖𝑡 1023
Therefore the temperature reading for any given analogue input value can calculate as follows, 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑉𝑎𝑙𝑢𝑒 =
𝑅𝑒𝑎𝑑𝑖𝑛𝑔 𝑜𝑓 𝑡ℎ𝑒 𝑎𝑛𝑎𝑙𝑜𝑔𝑢𝑒 𝑝𝑖𝑛 × 510.2041 ℃ 1023
There is two temperature sensors installed in the system so the temperature value will be the mean of those two sensor values. The reason is only one fan is going to operate. If there are much fans temperature of separate areas could be measured individually and the fan speeds can be adjusted according to the area temperature.
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A 12V DC fan is going to be used in my application. The fan cannot be controlled directly by the microcontroller. An operation of a fan may use significant amount of current. Microcontrollers cannot handle large currents. Therefore direct controlling is not possible. So need any power controlling method to control the fan motor. L293D is a motor controlling IC that can operate with in a voltage range of 4.5V to 36V up to a maximum current of 1A. I am using a 12V DC motor so it is possible for my application (Appendix 12). L293D IC has two supply voltage ports one is for supply power to the logic circuit and other input should give the required motor voltage. The following diagram shows the L293D IC connections with the atmega 2560 IC (figure 71). This IC can control two motors with different PWM duty cycles.
Figure 71 L293D motor controller connections with the atmega 2560 Drawn by using Proteus simulation software
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As I mentioned in above paragraphs when the temperature of the system changes the fan speed must change. Charging and discharging optimal temperature ranges different from each other. Therefore when dividing temperature groups there should be different temperature ranges for both charging and discharging. The speed of the motor is controlled by the PWM signal generated by the microcontroller. To control the speed, duty cycle of the PWM signal should be changed. The following figure shows, with different duty cycles how a PWM signal varies.
Figure 72 Change in PWM signal according to duty cycle (Arduino, 2016)
The speed of the motor can be controlled by changing the PWM duty cycle. For higher duty cycles the motor speed will be max and for lower duty cycles the speed will be low. PWM is the easiest method of controlling the speed of a motor. Therefore for different fan speeds I need to specify different PWM duty cycles in the coding. The PWM output is given as an analogue out and the duty cycle of any PWM signal varies within 0 – 255 digital values.
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Following tables shows different system temperature groups, when charging and discharging of the battery. Table 12 shows temperature groups when charging and table 13 shows temperature grouping when discharging. Charging temperature must be in between 0 oC to 45 oC. So I divide that temperature range into seven groups. Fan will off in the first group. Lower temperature state that the system circuit’s power dissipation is lower. Therefore no need of reducing the temperature by operating the fan. Then the fan speed will increase from group two to group five by increasing the each group’s PWM duty cycle by 20%. That means in the group five fan speed is in its maximum value. If the system temperature rise more than 45 oC the battery charging should be stopped. The reason is over the designed temperature typical battery reactions could be changed and damaged the battery. Therefore over the maximum temperature value the charging process must be stopped. But the fan should run continuously to lower the temperature to a middle range value. Thereafter a command can give to restart the charging process. Temperature grouping for charging Temperature range o
C
Description or Action
Percentage duty cycle
PWM duty cycle value (from 255)
0 oC to 20 oC
Fan off
0
0
20 oC to 25 oC
Speed 01
20%
51
25 oC to 30 oC
Speed 02
40%
102
30 oC to 35 oC
Speed 03
60%
153
35 oC to 40 oC
Speed 04
80%
204
40 oC to 45 oC
Maximum speed
100%
255
100%
255
More than 45 oC
Emergency stop Charging process Table 12
Fan speed variation for different temperature groups when charging
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Table 13 is about the discharging temperature grouping. Discharging temperature range is greater than the charging temperature range. So fan speeds must change in the discharging process because the temperature grouping is different. Discharging temperature range of the battery is -20 oC to 60 oC. Lower temperature value are not necessary because our country’s minimum temperature is more than 0 oC. So in grouping I have not considered minus values. Similarly in charging at the first temperature range the fan will stop operating. After that speed increase with a 20% duty cycle increment in each group. The maximum temperature is 60 oC, but if the electric vehicle is travelling at that time, a warning should give to the driver about the system heating early to take immediate action. So in my system the overheating warning will give at 55 oC. When the maximum temperature reaches the discharging processes will be stopped immediately. Temperature grouping for discharging Temperature range o
C
Description or Action
Percentage duty
PWM duty cycle
cycle
value (by 255)
0 oC to 20 oC
Fan off
0
0
20 oC to 30 oC
Speed 01
20%
51
30 oC to 35 oC
Speed 02
40%
102
35 oC to 40 oC
Speed 03
60%
153
40 oC to 45 oC
Speed 04
80%
204
More than 45 oC
Maximum speed
100%
255
100%
255
100%
255
If the temperature is more than 55 oC More than 60 oC
System Overheated Warning given Emergency stop Discharging process Table 13
Fan speed variation for different temperature groups when discharging
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4.6 Cell Balancing System Design For the balancing circuit I used the double-tiered switched capacitor method. As in the literature review in double-tiered switched capacitor for an n number of cells the circuit needs 2n number of switches. I am using power MOSFETs switches for the balancing circuit. The following figure shows how the MOSFETs are connected with series battery cell pack. Q1 2SK2553L
V1 3.7V
MOS_01 Q3 2SK2553L
MOS_02 Q4 2SK2553L
V2 3.7V
MOS_03
Q5 2SK2553L
MOS_04 Q6 2SK2553L
V3 3.7V
MOS_05 Q7 2SK2553L
MOS_06
Figure 73 Connection of MOSFETs in the balancing circuit Drawn by using Multisim software
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In the above figure (figure 73) 2SK2553L MOSFET’s are selected only for the simulation. The 2SK2553L has a maximum drain source voltage of 60V up to a maximum current of 50A. For the real design of the system a MOSFET has to be selected. The selection process will describe below by a separate heading. Operation of MOSFETs directly from the microcontroller is not suitable. Because if one of the MOSFET damaged then there is a risk to damage the controlling IC also. If the controlling IC fails all the controlling processes will stop. Therefore needs isolations in between the MOSFET and the microcontroller. In most of the micro controllers the output maximum voltage is 5V. Typically in isolation ic’s the minimum operating voltage is more than 5V. Therefore we need to amplify the output signal of the microcontroller. So a signal amplifier is also important.
4.6.1 Selection of MOSFETs As I mentioned in the literature review MOSFET’s has different operating characteristics to the different values of drain, source and gate operating voltages. So first of all I have to identify the limitations of my circuit before selecting a MOSFET. In my circuit 3 MOSFET’s are connected to batteries by its drain terminal and other three MOSFET’s are connected by its source terminal. In my application I have used N-channel MOSFET’s. The reason is to turn on a N-channel MOSFET a positive gate voltage signal should supply. But to turn on a P-channel MOSFET we have to supply a negative voltage to its gate. It is easy to supply a positive voltage signal than a negative signal to operate MOSFETs. So that is the main reason that I choose N-channel MOSFET’s for my application. In my application maximum drain source voltage will be 3.6V. Since I am using 3.6 Liion batteries. Most of the MOSFET’s the optimum gate source voltage value is 10V. In my sample model the drain current will be less than 10A. A datasheet of a MOSFET’s give vital knowledge about its characteristics. There are different graphs available in a datasheet. Among them the graphs that show the variation of the drain current according to the Drain-Source voltage and the Gate-Source voltage is more important to the MOSFET selection process. ~ 116 ~
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The following figures shows sample graphs of Drain Current vs the Drain-Source voltage (figure 74) and drain Current vs the Gate-Source voltage (figure 75).
Figure 74 Graph of Drain Current vs the Drain-Source voltage Appendix 13
Figure 75 Graph of Drain Current vs the Gate-Source voltage Appendix 13
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The following table shows terminal voltage characteristics of five different MOSFETs. Drain current capabilities are compared in the following table. Maximum MOSFET
Continuous Drain Current
Model
Rating o
FQP30N06L
Maximum Drain-Source
Gate-Source
available
Voltage (VDS)
Voltage (VGS)
Drain Current at 25 oC (ID)
o
25 C
100 C
32A
22.6A
5V
50A
6V
Less than 55A
8V
Less than 55A
5V
Less than 70A
6V
Less than 80A
8V
Less than 80A
5V
Less than 20A
6V
Less than 30A
8V
Less than 30A
5V
Less than 24A
6V
Less than 44A
8V
Less than 48A
5V
Less than 6A
8V
Less than 16A
current at 55 oC
10V
Less than 18A
is
5V
Less than 6A
8V
Less than 22A
10V
Less than 24A
5V
Less than 3A
8V
Less than 15A
10V
Less than 20A
5V
Less than 3A
8V
Less than 18A
10V
Less than 30A
2V
4V
STP30NF10
35A
25A 2V
4V
BUZ71A
Maximum continuous
13A
IRF640N
2V
4V
25 oC
100 oC
18A
13A
2V
4V
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Maximum
6ET011
5.5V
Less than 0.3A
8V
Less than 0.8A
Drain Current
10V
Less than 0.8A
at 25 oC is
5.5V
Less than 0.3A
8V
Less than 2.6A
10V
Less than 2.6A
continuous
7.4A
2V
4V
Table 14 Comparison of MOSFET characteristics Appendix 13, Appendix 14, Appendix 15, (APATEL3, 2004), (Unisonic, 2014)
In my balancing circuit as I mentioned in the current sensing topic the maximum balancing current will be less than 15A. I am using CGR18650CG li-ion battery that has maximum and minimum voltages of 3.6V and 2.5v respectively for my sample implementation. Therefore in the above table I have compared the maximum drain current rating in between gate voltage rang of 2V and 4V. If we take the 7N60 MOSFET it has current rating less than 15A so it is not suitable for my application. At 25 oC IRF640N MOSFET has compatible characteristics for my requirement but the maximum current rating at 100 oC is 13A. That is my marginal requirement so IRF640N MOSFET is not suitable. BUZ71A MOSFET has better drain current characteristics than the IRF640N MOSFET but its maximum Drain current at 55oC is 13A. It can use for my system implementation. But energy could be wasted. Energy efficiency is most important in electric vehicle applications therefore BUZ71A MOSFET is not suitable. FQP30N06L and STP30NF10 MOSFETs have the best drain current capabilities for my application. Considering the availability of above MOSFETs I have selected both FQP30N06L and STP30NF10 MOSFETs as my implementation section. But I am going to use one of those MOSFETs considering the availability.
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MOSFETs are controlled by a microcontroller. The microcontrollers typical PWM out is 5V. FAP30N06L MOSFET can operate by using 5V but its drain current capabilities are higher for if operating gate voltages 6V or higher than 6V. Similarly in STP30NF10 MOSFET for gate voltages 6V of higher than 6v has higher drain current margin. So I am going to supply 6V or more voltage for the gate of the MOSFET. Therefore the signal from the microcontroller should amplify to get a voltage more than 5V. Moreover as I mentioned because of safety purposes MOSFETs are not going to operate directly by the microcontroller. So the microcontroller signal needs to isolate. 4.6.2 Isolation of the MOSFET Controlling Signal In my system I am going to use opto-isolators to isolate the microcontroller signals. In the literature review I have described about opto-isolators. Opto-isolators are suitable for high speed applications. The operating frequencies of my balancing circuit would be higher. There are three types of isolation methods available. They are capacitive isolation, inductive isolation and optical isolation (Instruments, 2006). Among them opto-isolation is the best method of isolation suitable for my project. I am using 6N136 optocoupler manufactured by Vishay Semiconductors to isolation. The following figure shows the optocoupler wiring circuit designed by using “multisim”. +5V
XFG1 10kΩ
R2 COM
U1 8 7 6
Optocopuler_output
2 3
5
6N136 R3 330Ω
R1 330Ω
+5V V1 6V
Figure 76 Optocoupler wiring circuit Designed by ‘Multisim’ software
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In the optocoupler input I have placed a 330 ohm resister in series with the optocoupler. Typically 6n136 optocouplers’ input voltage drop will be 1.33V according to the data sheet attached in appendix 16. But the maximum will be 1.9V. 330 ohm resister will hold the voltage difference between the optocoupler inputs constant if the signal is voltage varied. In the optocoupler output resisters are placed to limit the current passing through the optocoupler output thus the maximum output current of 6N136 optocoupler is 16mA according to the datasheet. I have done simulations for the 6N136 optocoupler by using the multisim simulation software. The following figure shows how the oscilloscope is connected to the circuit with the signal generator. Signal generator is used to generate a substitution PWM signal. +5V
XFG1 10kΩ
R2 COM
U1 8 7 6
Optocopuler_output
2
XSC1 3
5
Tektronix
6N136 R3 330Ω
R1 330Ω
P G
1 2 3 4
T
+5V V1 5V
Figure 77 Optocoupler simulation circuit Simulated by ‘Multisim’ software
Oscilloscopes’ 1st and 2nd ports are connected to the input and the output of the optocoupler respectively. As the input signal, signal generator is adjusted to generate a 5V PWM signals with different user selectable frequencies. Simulation is done for 2Hz, 200Hz and 2 kHz. I have selected these frequencies because the balancing frequencies of a typical cell balancer lies in between those frequencies.
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Simulated graphs for both 5V input and output voltages for 2Hz, 0.2 and 2kHz frequencies.
Figure 78 Optocoupler simulation for 2Hz input signal Simulated by ‘Multisim’ software
Figure 79 Optocoupler simulation for 200Hz input signal Simulated by ‘Multisim’ software
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Figure 80 Optocoupler simulation for 2 kHz input signal Simulated by ‘Multisim’ software
Figure 81 Optocoupler simulation Simulated by ‘Multisim’ software
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In the oscilloscope top signal is the input signal and the bottom one is the output signal. In every simulation there was no a considerable difference between input and output signals. So according to the simulation results this optocoupler circuit is suitable in my frequency range. Microcontrollers are designed to operate in lower current rates. The maximum current output of a PWM output is typically 30mA. The maximum value pin current 40mA. But in the atmega 2560 processor the maximum current rating for all PWM pins is 200mA. I am using most of PWM pins for my application. The following figure shows the current reading of the optocoupler input when the signal generator is connected. Signal generators current is controlled by own to resist damages. But if a microcontroller connected to the optocoupler input there will be more current in the input pin than this application.
Figure 82 Optocoupler simulation input current in signal generator Simulated by ‘Multisim’ software
Due to safety reasons I have designed an amplifier module to support the microcontroller to deliver signals to the microcontroller.
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4.6.3 Design of Signal Amplifier for the Optocoupler IC As I said before the amplifier circuit is designed to protect the microcontroller from the high sourcing currents. The following figure shows the designed amplifier circuit for the optocoupler. +15V
R2
B
U1A
8
Vin
3
10kΩ 2
A
Amplified Signal Output TL082ID
4
PWM Signal Input
Vout
1
-15V 10kΩ R1
+15V
R3 10kΩ
V1
V2
15V
15V
-15V
Figure 83 Amplifier design for the optocoupler Designed by ‘Multisim’ software
Amplifier is supplied +15V and -15V as the operating voltage. Amplifier model can be obtained by using following computation process. There is no current flow through A to B due to high internal resistance of the amplifier. Therefore; 𝑉𝑖𝑛 = 𝑉𝐵
By applying KCL for the A node. 𝑉𝑜𝑢𝑡 − 𝑉𝐴 𝑉𝐴 − 0 = 𝑅1 𝑅3
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According to op-amp characteristics VA = VB. therefore; 𝑉𝑜𝑢𝑡 − 𝑉𝐵 𝑉𝐵 = 𝑅1 𝑅3 𝑉𝑜𝑢𝑡 − 𝑉𝑖𝑛 𝑉𝑖𝑛 = 𝑅1 𝑅3 𝑉𝑜𝑢𝑡 = 𝑅1 ×
𝑉𝑖𝑛 + 𝑉𝑖𝑛 𝑅3
𝑉𝑜𝑢𝑡 = 𝑉𝑖𝑛 (1 +
𝑅1 ) 𝑅3
In my application R1 = R2; So, 𝑅 𝑉𝑜𝑢𝑡 = 𝑉𝑖𝑛 (1 + ) 𝑅 𝑉𝑜𝑢𝑡 = 2 × 𝑉𝑖𝑛
By changing the value of R1 the amplifier output voltage can be changed. The following figure (figure 84) shows he simulated results of the amplifier. Top signal is the signal output and the bottom signal is the input signal.
Figure 84 Simulation results of the amplifier Simulated by ‘Multisim’ software
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XSC1
I: 44.4 pA I(p-p): 10.6 pA I(rms): 47.6 pA I(dc): 47.6 pA I(f req): 10.0 Hz
V: 0 V V(p-p): 5.00 V V(rms): 3.54 V V(dc): 2.50 V V(f req): 10.0 Hz
PR1
+15V
P G
3
10kΩ
PR2
A
V
1
PR3
2
T
R4
PR4
330Ω
A
LED1
-15V
COM
R1 PR5 V: 1.28 V V(p-p): 5.10 V V(rms): 3.54 V V(dc): 2.50 V V(f req): 10.0 Hz
I: -960 uA I(p-p): 22.2 mA I(rms): 14.0 mA I(dc): 9.93 mA I(f req): 10.0 Hz
10kΩ
V
V: 2.56 V V(p-p): 10.2 V V(rms): 7.07 V V(dc): 5.00 V V(f req): 10.0 Hz
TL082ID
4
XFG1
1 2 3 4
U1A
8
R2
V
Tektronix
R3 10kΩ +15V
V1
V2
15V
15V
-15V
Figure 85 Simulation circuit of the amplifier Simulated by ‘Multisim’ software
The above figure (figure 85) shows the simulation of amplifier circuit with the signal generator and the oscilloscope. As in the figure 85 the current of the signal generator is 10.6pA (max) while the output current of the amplifier is 22.2mA (max). Therefore there will be protection for the microcontroller from the high sourcing current. I have selected TL081 op-amp IC for my implementation and the datasheet is attached in appendix 17.
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4.6.4 Selection of Capacitors in the Balancing Circuit In double-tiered switched capacitor method battery energy is transferred to capacitors. When the voltage gap of cells increases the balancing energy also increase. So capacitors should be capable of charge different amount of energy in different frequencies. The following figure shows the cell balancing MOSFET circuit with 20mF capacitors. Q1 2SK2553L
V1 3.7V
MOS_01 Q3 2SK2553L
MOS_02 Q4 2SK2553L
V2 3.7V
C1 20mF
MOS_03
C3 20mF
Q5 2SK2553L
MOS_04 Q6 2SK2553L
V3 3.7V
C2 20mF
MOS_05 Q7 2SK2553L
MOS_06
Figure 86 Double-tiered switched capacitor circuit Drawn by ‘Multisim’ software
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Capacitor selection of the circuit is carried out by using the help of a research done in (Daowd et al., 2013). The following graph shows capacitor charge with respect to the capacitor value.
Figure 87 Capacitor charge with respect to the capacitor value (Daowd et al., 2013)
In my system I have selected 20mF capacitors. For the 20mF capacitor the charging energy is margin to the other maximum value of charge according to the graph. A value capacitance value more than 20mf is good. I select this value as a sample value in my system. I will change the capacitance value by analyzing my system by using the 20mf capacitor in the future. In the analysis I have implemented 3.4 equation to calculate transferring energy for a certain voltage gap. The pulse charge energy of a capacitor can be found by the equation 3.10. Those have to be simulated in ‘Matlab software’ to get a range of results because there are more than one unknown variables. In the future development ‘Matlab’ simulation will be performed.
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4.6.5 Switching Algorithm of the Cell Balancing Circuit There are six MOSFETs in the balancing circuit. Those six MOSFETs are divided into two groups. Same PWM signal is given to MOSFETs in the same group. Two groups are divided as follows. Group 01
MOS_01, MOS_03, MOS_05
Group 02
MOS_02, MOS_04, MOS_06
The following diagram shows PWM signals of each MOSFET group. PWM signal of Gropu 01 MOSFETs 1 0.5 0 0
0.5
1
1.5
2
2.5
3
3.5
4
3
3.5
4
PWM signal of Gropu 02 MOSFETs 1
0.5 0 0
0.5
1
1.5
2
2.5
Figure 88 PWM signals of each group of MOSFETs
Each signal has given a duty cycle of 40% but the Group 02 signal is delayed by half of a cycle. Signals cannot give 50% duty cycle because when switching there could be short circuits. So the duty cycle of each signal should be less than 50%.
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When the cell voltage gap is rising cell balancing time also increases as mentioned before. By using different balancing frequencies we can overcome this issue. In the analysis I have implemented the following relationship (equation 3.4) between cell voltage difference and the balancing energy. 𝑻𝒓𝒂𝒏𝒔𝒇𝒆𝒓𝒓𝒆𝒅 𝒑𝒐𝒘𝒆𝒓 (𝑱) =
𝑪𝒃𝒂𝒕 × 𝑲𝟐 × 𝟑. 𝟔 𝑽𝒎𝒂𝒙 − 𝑽𝒎𝒊𝒏
Matlab simulation for the above equation as follows. k = 0:0.0001:0.2; T = (2250.*k.*k*(3.6))/(1.1); figure plot(k,T); xlabel('Voltage Diffrence Between Cells'); ylabel('Transfering Cell Energy'); grid on;
Figure 89 Transferring cell energy vs cell voltage difference Simulated by using Matlab Software
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According to the (Daowd et al., 2013) the balancing frequency and the transferring energy for a period of time displayed in the below figure.
Figure 90 Capacitor charge with respect to the capacitor value (Daowd et al., 2013)
So we can see that when increasing the balancing frequency the energy transfer also increasing. But maximum increment can be obtain only for a certain range of frequencies. In this example they have used a 100mf capacitor. In my system I am using 20mF capacitors. Therefore as my balancing frequency I am going to provide a value between 200Hz to 500Hz. In my sample implementation I am not going to use different frequencies for different voltage gaps. A fixed frequency value will be provided to the balancing MOSFETs. For the future development I am going to develop this system to balance in different frequencies. In this balancing circuit charge is transferred between every cell in the stack when the MOSFETs are switching. In the next page switching process is described using two way switches. Switches are acting as a substitute to the MOSFETs.
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In the following diagram (figure 91) S1 switch is connected with path A and S2 and S3 switches are connected with path B and C respectively. This situation is similar to the MOSFETs operations in group A. when the signal is supplied capacitors will charge up to 40% of duty cycle. When charging X node will have a maximum voltage of 2.6V the voltage of the V1 battery. Similarly Y and Z nodes will get the voltages of B point and the C point. MOSFETs are act like as a resister and as a connection switch with capacitors. According to the below example (figure 91) X, Y and Z point will have voltages of 7.4V, 4.8V and 2.5V respectively. Therefore the C1, C2 and C3 capacitors are charged by 2.6V, 2.3V and 4.9V respectively. After a half of a frequency time period the switching signal will move to Group 02 to perform the cell balancing. The balancing cycle is described in the next page.
S1
X
A V1 2.6V
Key = Space C1 20mF
B
C3 20mF
S2 V2 2.3V
Y
C2 20mF
Key = Space
C V3 2.5V
S3
Z
D Key = Space
Figure 91 Operation of group 01 MOSFETs Drawn by using Multisim software
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When the Group 02 MOSFETs are switched (figure 92) for a duty cycle time of 40% X, Y and Z points will get voltages of B, C and D nodes. In the above process capacitor are charged according to the voltages of A, B and C points. Therefore three will be voltage differences between cells and capacitors. When S1, S2 and S3 switches connected to B, C and D the voltages of X, Y and Z will be 4.8V, 2.5V and 0V respectively.
Previous Voltage Points
Present Voltage with
with respect to VZ =
respect to VZ = 0V
2.5V X
Y
7.4V – 2.5V
4.8V
= 4.9V 4.8V – 2.5V
2.5V
= 2.3V
Voltage difference previous and present 4.9V – 4.8V = 0.1V 2.3V – 2.5V = - 0.2V
Table 15 Capacity voltage differences when balancing
Therefore the current will flow from C1 capacitor to V2 battery because VXB = 0.1V. The voltage difference between Y and C points VYC = -0.2V. Therefore the current will flow from the V3 battery to the capacitor block. Therefor the excess energy of the V1 and V3 battery will directly transform to the V2 battery. By doing this process continuously all the three cells will balance equally. The balancing time will also be minimized. The reason is all the cells are balancing in same time and it is not an individual cell balancing process.
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X
A V1 2.6V
Key = Space C1 20mF
B
C3 20mF
S2 V2 2.3V
Y
C2 20mF
Key = Space
C V3 2.5V
S3
Z
D Key = Space
Figure 92 Operation of group 02 MOSFETs Drawn by using Multisim software
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Following figures (figure 93 & figure 94) shows the complete cell balancing circuit without the microcontroller.
Q1 2SK2553L
V1 3.7V
MOS_01 Q3 2SK2553L
MOS_02 Q4 2SK2553L
V2 3.7V
C1 20mF
MOS_03
C3 20mF
Q5 2SK2553L
MOS_04 Q6 2SK2553L
V3 3.7V
C2 20mF
MOS_05 Q7 2SK2553L
MOS_06
Figure 93 Full circuit of MOSFET connections with isolation part 1 Drawn by using Multisim software
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+5V
+15V
Micro_controller_PWM_port_1
3
U2
10kΩ
2
1 2
8 7 6
3
4
TL082ID -15V
MOS_01
5
R6 330Ω
R1 R4 10kΩ
R2 10kΩ
U1A
8
R3
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R5 330Ω
10kΩ GND
+5V
+15V
Micro_controller_PWM_port_2
3
U3
10kΩ
2
1 2
8 7 6
3
4
TL082ID -15V
MOS_02
5
R12 330Ω
R8 R10 10kΩ
R7 10kΩ
U4A
8
R9
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R11 330Ω
10kΩ GND
+5V
+15V
Micro_controller_PWM_port_3
R13 10kΩ
U6A
8
R15
3
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10kΩ
2
1 2
3
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TL082ID -15V
MOS_03
5
R18 330Ω
R14 R16 10kΩ
8 7 6
6N136
R17 330Ω GND
10kΩ
+5V GND +15V
+5V
+15V
8
R21 Micro_controller_PWM_port_4
3
U7
10kΩ
2
1 2
8 7 6
3
4
TL082ID -15V
MOS_04
5
R24 330Ω
R20 R22 10kΩ
R19 10kΩ
U8A
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R23 330Ω
10kΩ GND
+5V
+15V
Micro_controller_PWM_port_5
3
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2
1 2
8 7 6
3
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MOS_05
5
R30 330Ω
R26 R28 10kΩ
R25 10kΩ
U10A
8
R27
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R29 330Ω
10kΩ GND_4
+5V
+15V
U11 2
1 2
8 7 6
3
TL082ID -15V
R32 R34 10kΩ
R31 10kΩ
U12A
3
10kΩ
4
Micro_controller_PWM_port_6
8
R33
MOS_06
5
R36 330Ω
6N136
R35 330Ω
10kΩ GND_5
Figure 94 Full circuit of MOSFET connections with isolation part 2 Drawn by using Multisim software
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4.7 System Interface LCD Design In my sample implementation I have used a LCD display to present some system measurements. In an electric car to display information about its electrical systems, an instrument cluster is used. Typically the system temperature, battery charge, drivability and other safety information are displayed in the instrument cluster. In my system the operator should know what is happening inside the electrical circuits. So system information should be provided to the user. There are current sensors, voltage sensors and temperature sensors are installed in my system. This is a cell balancing system when cell balancing, battery voltages should come to a marginally equal value. It can only be seen with a display that presents voltages of each cell. Therefore I am going to display all cell voltages, the total battery voltage and the available battery capacity in my display module. There is a current sensor installed in my system. The discharge or charged current is also a valuable information. So the battery current also displayed. I have placed two temperature sensors in my model. So the average temperature value of the system is also displayed. The following figure shows the connection between the 4*20 LCD display and my microprocessor. There is a potential meter attached to the display. By that the LCD brightness can be controlled. Typically all the required pins of the LCD display are connected to the microcontrollers’ digital pins.
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Figure 95 Microcontroller connections for 4*20 LCD display Drawn by using Proteus simulation software
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4.8 System Power Supply In an electric vehicle there is a separate battery to supply power to the electrical systems of the car. Typically as the auxiliary battery lead-acid battery is used. So to simulate that I have used a separate battery to supply power to the electrical system. Li-ion batteries are discharged by a motor to simulate the motor operation in the electric car. The supplied power is 12V but it has to be reduced to give supply to the other modules such as signal amplifier, microcontroller and for the other sensors. So a power distributing circuit has to be made with reduced voltage supplies to the circuits. In my circuit modules I have used following voltages. System module
Used voltages
Current sensor
+5V
Voltage sensor
+15V & -15V
Temperature sensors
+5V
To arduino
+12V direct
To MOSFET controlling
+15V, -15V and +5V
circuit
Table 16 Operating voltages of different modules
There for a +5v output is made by using LM7805 voltage regulator IC. The datasheet of the LM7805 is attached in the appendix 18. Supplying voltages of op-amp is +15V and -15V. But I have only given a 12V battery power to the system. So to boost the 12V voltage to 15V a boost converter is needed. For the boost converter I am going to use LM3224 step-up controller IC. The circuit will be made in future implementation and for my sample a boost converter module is used for supply power to the amplifiers.
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Chapter 05 System Implementation & Testing
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5.0 System Implementation and Testing 5.1 PCB Designs of the System Circuits In my sample battery management system there are some circuits that are needed to be printed. First of all we have to draw those circuits by using a proper software for each component’s real dimensions. I am using eagle cad software to draw my PCB designs. Eagle is a user friendly software. When designing PCB’s first we have to draw the schematic diagrams of the circuits. After that the schematic can be transferred to the board drawing platform. Then in the board we can place components anywhere that we want. But we have to consider the heating conditions and temperature effects when placing electrical components. Afterwards the paths can be drawn manually or by using AutoRoute function. 5.1.1 Designing of the Voltage Sensing Circuit PCB In the voltage sensing PCB design separate connected used to connect the each cell terminals to the measuring op-amps. There are three series cell packs and therefore four connecting points are available. For power the op-amps two voltage input terminals were added. In my simulation circuit diagram in the system design I have used OPA4277PA op-amp. But in my PCB design I have used OPA277P op-amp. There is no difference between these op-amp types. OPA4277PA is a chip that has four op-amps inside it. OPA277P is a single op-amp IC. Single op-amp is easy to place in the PCB when designing. To reduce the space of the circuit I have used SMD based capacitors and transistors. Through-hole resisters and capacitors need some more space and by adding SMD type components space can be minimized. The circuit is designed in both sides due to complexity of the circuit paths. SMD type components are soldered in one side of the PCB while other components like op-amps placed the other side of the PCB.
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The following figure shows the schematic design of the voltage measuring circuit (figure ##).
Figure 96 Schematic design of the voltage measuring circuit Drawn by using eagle CAD
The below figure (figure ##) shows the full design of the voltage measuring circuit board.
Figure 97 Circuit board design of the voltage measuring circuit Drawn by using eagle CAD
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The following two images presents the separate view of the top view and the bottom view of the voltage measuring circuit.
Figure 98 Top view of the Voltage measuring PCB Design Drawn by using eagle CAD
Figure 99 Bottom view of the voltage measuring PCB Design Drawn by using eagle CAD
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5.1.2 Cell Balancing Circuit PCB Design Cell balancing circuit PCB design is complex than the voltage measuring circuit PCB design. There are heat generating power MOSFETs in this circuit. So before thinking of the other components those must be placed on the circuit board by giving a good air flow area. Then the other components placed on the board in a proper a manner. Because if there is any fault the system is easy to test and identified the fault if the components placed well on the circuit board. As in the voltage measuring circuit board SMD based resisters and capacitors are used in cell balancing circuit also to reduce the space that taken by the through-hole resisters and capacitors. There are three high power capacitors placed on the board for the cell balancing criteria. For the power contactors large connectors used and for the PWM inputs standard header pins are used. A SMD based led is placed on the circuit board.
Figure 100 Schematic design of the cell balancing circuit Drawn by using eagle CAD
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The top view and the bottom views of the cell balancing PCB design have shown in the below figures.
Figure 101 Top view of the cell balancing PCB Design Drawn by using eagle CAD
Figure 102 Bottom view of the cell balancing PCB Design Drawn by using eagle CAD
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Chapter 06
Conclusion
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6.0 Conclusion Battery management systems’ main task is the cell balancing. Electric cars need maximum power efficacy due to limitation of battery capacity. There are several types of batteries available for electric vehicles. Among them Li-ion battery is the best battery that available for electric vehicles. Li-ion batteries damage if they are over charged or over discharged. So a management of batteries are essential for safety and for the vehicle performance. There are various battery balancing methods available. In my project I have selected the double-tiered capacitor method as my cell balancing method. A model based cell balancing system is designed for three cells as the first implementation. The system will be developed in future researches. SOC is the main variable that using for the cell balancing. SOC cannot be directly measured. It has to be estimated. To estimate the SOC temperature, discharging or charging current rate, battery aging and cell voltage is needed. For accurate estimation of SOC battery model based SOC estimation is needed. In the future I am going to develop a battery model including voltage, temperature, current and cell aging characteristics. In my system I have designed a voltage measuring module, a current sensing module and a temperature sensing module with cooling. I have not considered the battery aging effect for this project. I am going to develop battery aging estimation, SOH measurement in the future. I am using OCV method for the estimation of SOC. When charging and discharging the battery voltage is varied. Therefore I have only designed my cell balancing system for a one charging or discharging rate. A battery model based structure will be developed in the future. An arduino based battery management system is made. Cells will be balanced by same frequency due limitations of the atmega 2560 processor. PWM frequency changing in the atmega 2560 processor is cannot be performed. Frequency changing is available in PIC microcontrollers. For the future work a PIC microcontroller based management system is going to be made. Fast cell balancing can be achieved by changing balancing frequencies. Increment of voltage gap means there are more energy to balance. So with the increment of the voltage gap the balancing frequency needs to be increased.
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System safety is also a major task in battery balancing. For my system isolated MOSFET control circuit is developed. For the future work I am going to consider more on the system safety because for the actual development of the track day electric car safety of the diver and the cars electrical systems are essential. In an electric car hundreds of batteries are installed to power up the motor. Those batteries need to be distribute among the whole car. So a stability analysis is needed. Therefore for future development I am going to do a stability analysis for the real implementation of the electric car. Experimental test for the cell balancing circuit has not be performed in this project. But experimental testing of electrical systems is essential for electric car. Therefore I am going to do experimental tests in the future to test the system performance. So I will be able to improve my system performance and build a good battery management system in the future.
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References
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6 MOS transistor (2009) [online]. Available at: . Andrea, D. (2010) Battery management systems for large lithium ion battery packs [online]. Artech House. Available at: . APATEL3 (2004) HEXFET ® power MOSFET [online]. Available at: . Arduino (2016) PWM [online]. Available at: . Arduino_Current_limitations (2016) Arduino playground ArduinoPinCurrentLimitations [online]. Available at: . Becker, J., Schaeper, C. and Sauer, D.U. (2012) Energy management system for a multi-source storage system electric vehicle [online], pp.407–412 Available at: . Birke, P., Keller, M. and Prague, M.S. (2010) Electric battery actual and future battery technology trends division powertrain BU hybrid and electric vehicle introduction and short historical overview batteries first steps [online]. [Accessed 31 July 2016]. Available at: . Cao, J. and Emadi, A. (2011) Batteries need electronics. IEEE Industrial Electronics Magazine, 5(1), pp.27–35. CARY R. SPITZER and Vutetakis, D.G. (2008) TheAvionicsHandbook cap 10 [online] [Accessed 2 August 2016]. Available at: . Cheng, K.W.E., Divakar, B.P., Wu, H., Ding, K. and Ho, H.F. (2011) Batterymanagement system (BMS) and SOC development for electrical vehicles. IEEE Transactions on Vehicular Technology, 60(1), pp.76–88.
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References
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Daowd, M., Antoine, M., Omar, N., van den Bossche, P. and van Mierlo, J. (2013) Single switched capacitor battery balancing system enhancements. Energies, 6(4), pp.2149–2174. Daowd, M., Omar, N., Bossche, P.V.D. and Mierlo, J.V. (2011) Passive and Active Battery Balancing comparison based on MATLAB Simulation, 2011 IEEE(978-161284-247-9/11). Densmore, A. and Hanif, M. (2004) Determining battery SoC using Electrochemical Impedance spectroscopy and the extreme learning machine [online], pp.1–7 Available at: . Dhameja, S. and Dhameja, eep (2000) Electric vehicle battery systems. Boston: Newnes (an imprint of Butterworth-Heinemann Ltd ). Ehsani, M., Gao, Y., Gay, S.E., Emadi, A. and Gary, S.E. (2004) Modern electric, hybrid electric, and fuel cell vehicles fundamentals, theory, and design. Boca Raton, Flor.: CRC Press. Einhorn, M., Roessler, W. and Fleig, J. (2011) Improved performance of Serially connected Li-Ion batteries with active cell balancing in electric vehicles. IEEE Transactions on Vehicular Technology, 60(6), pp.2448–2457. GPH (2014) Field effect transistors (FET) simple model of MOSFET V gs < V t V gs ≥ V t MOSFET made VSLI (microprocessors and memories) possible. Excellent graphic showing four states of MOSFET for different Vgs and Vds [online]. Available at: . He, H., Peng, L. and Sun, F. (2004) Study on Power Battery’s Performance Evaluation. SAE TECHNICAL PAPER SERIES, 2004-01-0068. Hybrid electric and battery electric vehicles hybrid electric and battery vehicles (2008) [online]. Available at: .
~ 152 ~
Individual Project
References
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Hydride, N.M. (2013) Nickel metal hydride (NiMH) handbook and application manual [online]. Available at: . Instruments, N. (2006a) Isolation types and considerations when taking a measurement [online]. Available at: . Instruments, N. (2006b) Switch types and common terminology [online]. Available at: . Ishida, T. (2011) Feasible Study for the Availability of Electric vehicles for the Stable Operation in Power System Network. SAE International, 2011-39-7248. Juang, L.W., Kollmeyer, P.J., Zhao, R., Jahns, T.M. and Lorenz, R.D. (2015) Coulomb counting state-of-charge algorithm for electric vehicles with a physics-based temperature dependent battery model [online], pp.5052–5059 Available at: . Kawase, J. and Maebara, T. (2011) New Battery Monitoring Unit for HEV/EV Lithiumion Battery. SAE International, JSAE 20119273. Kim, C.-H., Kim, M.-Y. and Moon, G.-W. (2012) Individual Cell Equalizer Using Active-clamp Flybacl< Converter for Li-Ion Battery Strings in an Electric Vehicle. IEEE Vehicle Power and Propulsion Conference, pp.327–332. Kim, C.-H., Kim, M.-Y. and Moon, G.-W. (2013) A Modularized charge equalizer using a battery monitoring IC for series-connected Li-Ion battery strings in electric vehicles. IEEE Transactions on Power Electronics, 28(8), pp.3779–3787. Kota, O. and Balasubramanian, G. (2013) High voltage safety concepts for power electronic units. SAE Technical Paper Series. Kulkarni, A., Kapoor, A. and Arora, S. (2015) Battery packaging and system design for an electric vehicle. SAE International.
~ 153 ~
Individual Project
References
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Lecture: Lead-acid batteries how batteries work conduction mechanisms development of voltage at plates charging, discharging, and state of charge key equations and models (2009) [online]. Available at: . Li, S., Mi, C.C. and Zhang, M. (2013) A high-efficiency active battery-balancing circuit using Multiwinding transformer. IEEE Transactions on Industry Applications, 49(1), pp.198–207. LLC, M. (2010) Crude oil prices - 70 year historical chart [online]. Available at: . Lu, L., Han, X., Li, J., Hua, J. and Ouyang, M. (2013) A review on the key issues for lithium-ion battery management in electric vehicles. Journal of Power Sources, 226, pp.272–288. Mestrallet, F., Kerachev, L., Crebier, J.-C. and Collet, A. (2014) Multiphase Interleaved converter for lithium battery active balancing. IEEE Transactions on Power Electronics, 29(6), pp.2874–2881. Micea, M.V., Ungurean, L., Cârstoiu, G.N. and Groza, V. (2011) Online state-of-health assessment for battery management systems. IEEE Transactions on Instrumentation and Measurement, 60(6), pp.1997–2006. Moore, S.W. and Schneider, P.J. (2001) A Review of Cell Equalization Methods for Lithium Ion and Lithium Polymer Battery Systems. SAE TECHNICAL PAPER SERIES, 2001-01-0959. Nejad, S., Gladwin, D.T. and Stone, D.A. (2010) A microcontroller-based state-ofhealth estimator for lithium-ion batteries [online], pp.1–6 Available at: . Pattipati, B., Sankavaram, C. and Pattipati, K. (2011) System identification and estimation framework for pivotal automotive battery management system characteristics. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(6), pp.869–884.
~ 154 ~
Individual Project
References
6ET011
Piao, C., Wang, Z., Cao, J., Zhang, W. and Lu, S. (2015) Lithium-ion battery cellbalancing algorithm for battery management system based on real-time Outlier detection. Mathematical Problems in Engineering, 2015, pp.1–12. Qahouq, J.A.A. (2016) Online battery impedance spectrum measurement method [online], pp.3611–3615 Available at: . Sagar, A.D. (1995) Automobiles and global warming: Alternative fuels and other options for carbon dioxide emissions reduction. Environmental Impact Assessment Review, 15(3), pp.241–274. Schipper, L. (2011) Automobile use, fuel economy and CO2 emissions in industrialized countries: Encouraging trends through 2008?. Transport Policy, 18(2), pp.358–372. Shafiee, S. and Topal, E. (2009) When will fossil fuel reserves be diminished?. Energy Policy, 37(1), pp.181–189. Singh, P., Gaddam, V.R., Arey, S., Yang, Z., Fennie, C. and Reisner, D.E. (1999) Battery State-of-Charge Meters for High Performance Batteries Based on Fuzzy Logic Methodology. SAE TECHNICAL PAPER SERIES, 1999-01-2467. Solid-state Relays application guide (2002) [online]. Rockwell Automation. Available at: . Steinhorst, S., Shao, Z., Chakraborty, S., Kauer, M., Li, S., Lukasiewycz, M., Narayanaswamy, S., Rafique, M.U. and Wang, Q. (2016) Distributed reconfigurable battery system management architectures. 2016 21st Asia and South Pacific Design Automation Conference (ASP-DAC). Stockley, T., Thanapalan, K., Bowkett, M. and Williams, J. (2014) Design and implementation of an open circuit voltage prediction mechanism for lithium-ion battery systems. Systems Science & Control Engineering, 2(1), pp.707–717.
~ 155 ~
Individual Project
References
6ET011
Stuart, T., Fang, F., Wang, X., Ashtiani, C. and Pesaran, A. (2002) A Modular Battery Management System for HEVs. SAE TECHNICAL PAPER SERIES, 2002-01-1918. The electric vehicle world sales database (no date) [online]. Available at: . Thomas, C.E. (2009) Fuel cell and battery electric vehicles compared. International Journal of Hydrogen Energy, 34(15), pp.6005–6020. Unisonic, 7N60 (2014)
[online]. Unisonic. Available at:
. Wang, J.B. and Kao, D. (2014) Design and implementation of a battery module. IEEE. Xing, Y., Ma, E.W.M., Tsui, K.L. and Pecht, M. (2011) Battery management systems in electric and hybrid vehicles. Energies, 4(12), pp.1840–1857. Yarborough, B. (2007) Power metal strip ® resistors components and methods for current measurement [online]. Available at: . York, B. (2010) Transistor basics -MOSFETs [online]. Available at: . Young, K., Wang, C. and Wang, L.Y. (2013) Electric Vehicle Battery Technologies. in strunz, K. (ed.) Electric Vehicle Integration into Modern Power Networks. Yuan, S., Wu, H. and Yin, C. (2013) State of charge estimation using the extended Kalman filter for battery management systems based on the ARX battery model. Energies, 6(1), pp.444–470. Zhang, Z. and Sisk, B. (2013) Model-based analysis of cell balancing of lithium-ion batteries for electric vehicles. SAE International Journal of Alternative Powertrains, 2(2), pp.379–388. Zhao, C., Li, L., Wu, J. and Yuan, Q. (2007) Research on On-line Monitoring Methods of High Voltage Parameter in Electric Vehicles. SAE TECHNICAL PAPER SERIES, 2007-01-3466. ~ 156 ~
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Zhi-Guo, K., Chun-Bo, Z., Ren-Gui, L. and Shu-Kang, C. (2006) Comparison and evaluation of charge equalization technique for series connected batteries [online], pp.1–6 Available at: . Zhu, J., Sun, Z., Wei, X. and Dai, H. (2015) A lithium-ion battery Optimized equivalent circuit model based on Electrochemical Impedance spectroscopy. SAE Technical Paper Series.
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Appendix 01 Data sheet of 3.6V Li-ion 3070mAh battery
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Appendix 02 3.7V & 3000mAh Li-ion battery data sheet
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Appendix 03 3.6V & 2250mAh battery data sheet
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Appendix 04 Valance high current IFR26650PC battery cell data sheet
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Appendix 05 A123 system’s high current ANR26650m1-B Li-ion battery cell
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Appendix 06 Texas Instrument bq76PL536 battery monitoring IC
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Appendix 07 Linear Technologies LTC6802-1 battery monitoring IC
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Appendix 08 Performance curve of the 20kW BLDC motor
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Appendix 09 OPA277/OPA4277 operational amplifier
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Appendix 10 ACS 712 current sensor IC
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Appendix 11 LM35 temperature sensor
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Appendix 12 L293D motor Driver IC
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Appendix 13 Datasheet of FQP30N06L N-channel MOSFET
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Appendix 14 Datasheet of STP30NF10 N-channel MOSFET
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Appendix 15 Datasheet of BUZ71A N-channel MOSFET
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Appendix 16 6N136 High speed optocoupler
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Appendix 17 TL081 operational amplifier IC
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Appendix 18 Electrical characteristics of the LM7805 voltage regulator
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Appendix 19 LM3224 voltage step-up IC
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