May 25, 2016 - M.Tech. in Automotive Engineering Degree Program by ... CERTIFICATE ... Automotive Electrical System, Vehicle Performance, and Advanced ...
DISSERTATION
VESSiM – A PHYSICAL SYSTEM SIMULATION MODEL FOR VEHICLE ELECTRICAL SYSTEM
Submitted in partial fulfilment of the requirements of M.Tech. in Automotive Engineering Degree Program
by GOPAL ID. Number: 2014HT55015
Under the Supervision of RAJU G S Program Manager Tata Technologies Limited
Dissertation work carried out at Tata Technologies Limited, Pune
BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE Pilani (Rajasthan) India
May 2016
BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE, PILANI
CERTIFICATE
This is to certify that the Dissertation entitled VESSiM – A PHYSICAL SYSTEM SIMULATION MODEL FOR VEHICLE ELECTRICAL SYSTEM and submitted by GOPAL, ID No. 2014HT55015, in partial fulfilment of the requirements of AETT ZG629T Dissertation, embodies the bonafide work done by him under my supervision.
Signature of the Supervisor Name: Raju G S Designation: Program Manager Date: 25th May 2016
Abstract Stringent emission norms being enforced in near future and a steep increase in the fuel prices, have resulted in an increasing effort to optimize the fuel consumption and reduce greenhous gas emissions in vehicles with conventional Internal Combustion Engines. A reduction in fuel consumption, will always result in a reduction in toxic gas emissions. Micro and Mild Hybrid Systems, are the primary options to achieve the required target of reduction in fuel consumption. Micro and Mild Hybrid systems include functions like Engine Stop/Start, Intelligent Alternator Control, and Load Management, in which the engine output is optimized and wasteful running of the engine is prevented to improve the fuel efficiency. Intelligent Alternator Control is a function under Micro Hybrid Systems, in which the electrical energy generation, storage, and distribution is optimized, with the functions like battery SOC control, energy recuperation, and passive torque boost. The Alternator is controlled by a Electronic Control Unit, which sets the output voltage of the Altrnator, based on the control algorithm decisions. Development of such system functions is a complicated project. Particularly, the validation activities demand lot of effort and investment, due to time involved, specific test conditions, and specialized resources required. In such a scenario, Simulation of the vehicle performance promises to be a primary solution, as the approach helps in advancing the assessment, and even without the need for the implementation on a vehicle and physical tests on the same. Varius commercial tools are available for simulating the vehicle performance, and some tools even offer turnkey solutions. However, development of a custom simulation model is preferred, in order to address the special features of Micro Hybrid System Functions. In this project, an attempt is made to develop a physical system simulation model, VESSiM, in the physical modeling toolbox of Simscape®. Simulation model is targetted at simulating the performance of vehicle’s electrical system and estimating the fuel consumption of vehicle. Modeling scopes covers the physical modeling the of the vehicle under its longitudinal dynamics (including the entire power train modeling and accessory drives of the engine), complete electrical system, and associated control system and its tunning. The project follows the systems engineering approach for the development, and starts from the requirement analysis, and closes with the validation of the model. Although the model would be designed to have the flexibility to simulate different vehicle platforms with different specifications, scope for this submission is limited to configuring it for one vehicle platform, and validating the performance, on one specified drive cycle, for the simulation of Battery Charge Balance only. Micro Hybrid Functions are kept out of scope from this academic submission due to confidential information and time contraints as well. Parameter identification will be limited to requirements in the respective Simscape blocks. Comparison of the results of simulation with the actual vehicle performance will be carried out with the availabe test data, and there would be no scope for any physical tests being carried out to validate the model. Key Words: Modeling, Simulation, Simscape, Simulink, Fuel Consumption, Emission Control, Automotive Electrical System, Vehicle Performance, and Advanced Product Quality Planning.
Project Scope This project work started in the right time, when I was personally looking forward to enhance my skills in system modelling and simulation. In addition, there was a need felt in my team to enhance the current simulation models available for similar objectives must be enhanced. However, a full scale and business ready deployment effort for such projects requires lot of time and investment. Therefore, the scope for this academic submission is limited due to constraints of time, and in some cases the confidentiality of the design and Intellectual Property Rights. Scope and limitations are set out clearly as follows –
•
Development of the Vehicle Model to simulate the Battery Charge Balance, as Proof of Concept for the evaluation.
•
Model shall be ready for simulation of Intelligent Alternator Control system simulation.
•
Modelling and simulation of Micro/Mild Hybrid system functions is kept out of scope due to time constraints and confidentiality of the system design.
Acknowledgements After an intensive effort of completing the project and writing this thesis, I think this part of writing the acknowledgement is the most difficult. This is because of the sheer number of people who have contributed to this achievement and have supported me through the tough time I went through. Here is an effort to call each and every one of those and express my gratitude. Here is an attempt to pay gratitude to Prof. (Late) Y U Biradar. It was he who encouraged me to pursue Post Graduation after my graduation. I could not pursue then, due to some difficulties and things are complete only when I remember him today. A big share of thanks goes to my organization, Tata Technologies Limited. Tata Technologies Limited has always encouraged us to grow and has always provided enough opportunities to enhance our skills and expertise. The Strive program is just an icing on the cake, aiming to enhance our educational qualification. Therefore, my gratitude to Leadership and Development Team, and Senior Management Team is ineffable. Particularly I would like to thank Mr. Subhendu Ghosh, Executive Vice President, for envisaging this program and instituting it in our organization. I would like to express my gratitude to my seniors Mr. Pushkaraj Kaulgud (Program Manager), Mr. Sandip Umak (Sr. Project Manager), and Mr. Netaji Bhandare (Sr. Team Lead), for supporting me throughout this M Tech program. I must thank all my colleagues at Tata Technologies Limited, who appreciated my effort and felt proud about me. Here is a hope that I deserve their pride. I cannot forget my extended family at Tata Motors Limited. My gratitude and admiration for my reporting manager and my guide for this project and thesis Mr. Raju G S is boundless. He kindled the burning desire of continuous learning in me, by being a role model. It is his burning desire to keep learning, and childlike curiosity in new technologies and innovation which encouraged me to take up this effort of pursuing the post graduate education at this time of my life. He is one of those very few in the professional world who gives an unconditional support and encouragement to anyone who desires to learn and enhance himself. My colleagues at Tata Motors Limited, Mr. Ramakrishna Koduru, Mr. Satishkumar P who agreed to be onboard with me on this journey, as my project examiners, provided deep insights into the concepts before started working on the project, and also lent their expertise in evaluating my work and in addition improving it. I cannot forget Mr. Kapil Dongare, who in fact helped me a lot in my early days with Matlab and Simulink. Without his help I could not have learnt the basics of Matlab, which later on became an obsession and part of my everyday life. Mr. Prasad Rao Yerraguntla, shared his valuable insights on the Charging Systems with me which helped to achieve to deliver a better concept in this project work. The next big share of thanks goes to BITS Pilani and my faculty members who taught us through last 2 years. Particularly, I would like to thank Prof. Sarvesh Mahajan, who taught us the subject of Vehicle
Dynamics. His insights into the Longitudinal Dynamics of the vehicle helped me a lot in this project work, and writing my thesis. My sincere thanks and gratitude to Prof. Dinesh Wagh for all the support he has lent us throughout last 2 years. My family members always supported me in this effort. My mother and my grandparents stood with me as they did in those difficult times during my graduation, and this achievement would not have been possible without their blessings. My wife always stood with me throughout this program, and made sure that I am not bothered and stay concentrated. It is next impossible to express my gratitude to all of them. Finally, my gratitude to my Masters, Sri Aurobindo and The Mother. I dedicate this work at Their feet.
Gopal Athani Technical Lead – Engineering, Tata Technologies Limited.
Table of Contents Chapter No.
Title
Page Number
Introduction ……………...……………………………………………………
1
1.1
Mathematical Modelling ……………...………………………………………
1
1.2
Modelling Process and Simulation ……………………………………………
2
1.3
Systems Engineering ………………………………………………………….
6
1.4
System Modelling ...…………………………………………………………..
8
Advances in Vehicle Electrical Systems ……………………………………...
10
2.1
Background …………………………………………………………………...
10
2.2
Conventional 12 Volt Automotive Electrical System ………………………...
12
2.3
Micro Hybrid Systems ………………………………………………………..
19
2.4
Engine Stop/Start System ……………………………………………….........
21
2.5
Intelligent Alternator Control …………………………………..…………….
23
2.6
Development Approach for Micro Hybrid Systems ……………..…………...
34
Requirement Analysis …………………...……………………………………
37
3.1
Introduction to Requirement Management ………………..………………….
38
3.2
Requirement Gathering …………………..…………………………………...
39
3.3
Requirement Analysis and Traceability …………..…………………………..
45
3.4
Functional Validation Specifications ……………..…………………………..
70
Longitudinal Vehicle Dynamics ……………...………………………………
73
4.1
Introduction …………………………………………………………………...
73
4.2
Longitudinal Vehicle Dynamics ……………………………………………...
73
4.3
Powertrain Dynamics …………………………………………………………
78
Architectural Modelling ………………………………………………………
86
5.1
Macro Architecture ………………………...…………………………………
87
5.2
Drive Control System …………………………………………………………
87
5.3
Vehicle Plant Model …………………………………………………………..
89
5.4
Electrical System ……………………………………………………………...
92
1
2
3
4
5
6
Detailed Design and Development ……………………………………………
94
6.1
Vehicle Model …………………………………………………………………
95
6.2
Electrical System ………………………………………………………………
122
6.3
Data Visualization ……………………………………………………………..
127
Control System Design and Tuning …………………………………………..
129
7.1
Introduction ……………………………………………………………………
130
7.2
Control Problem Statement ……………………………………………………
130
7.3
Drive Control System ………………………………………………………….
134
7.4
Transmission Control System ……………………...………………………….
140
7.5
Control System Tuning ……………………...………………………………...
142
Validation of VESSiM ………………………………..……………………….
143
8.1
Introduction …………………………...……………………………………….
144
8.2
Drive Control System Validation ..…………….…………...………………….
144
8.3
Functional Validation ………………………………………………………….
149
8.4
Validation of Transmission Control ……………………………...……………
156
8.5
Battery Charge Balance Simulation …………………..……………………….
159
8.6
Other Systems ………………………..........…………………………………..
167
References …………………..…………………………………………………
173
7
8
List of Figures Figure #
Title
1
Process of Mathematical Modelling
2
Mass and Damper System
Page Number 2 2
Simulink®
3
Mass with Spring and Damper Modelled in
4
Deployment in Simscape®
4 5
5
Model Response
5
6
Illustration of Hierarchical System
6
7
Classification of Systems
7
8
Systems Engineering Model
8
9
Timeline of Implementation of Emission Norms
10
10
Solutions Implemented for Emission Control
11
11
Topology of Vehicle Electrical System
12
12
Exploded View of a Typical Automotive Alternator
12
13
AC Output from Stator
13
14
Rectified DC Output
13
15
Schematic of the Alternator
14
16
Construction of an Automotive Battery
15
17
Construction of an Automotive Starter Motor
16
18
Micro Hybrid System Architecture
19
19
Intelligent Battery Sensor
20
20
ESS System Function
22
21
ESS System Functional Behavior
22
22
Architecture of Micro Hybrid Control System
24
23
State Control Machine for AMS
26
24
Comparison of Battery Terminal Voltages
27
25
Effect of Battery State of Charge
28
26
Comparison of Charge Balance
31
27
Fuel Economy Improvement due to Intelligent Alternator Control System and Other Functions of Micro Hybrid System
31
28
Energy Recuperation Trend in a Micro Hybrid
32
29
Systems Engineering Model of MHS Development
34
30
Effort V/S Project Schedule
35
31
Test Input for Analyzing the Controller Response during Acceleration
70
32
Test Input for Analyzing the Controller Response during Deceleration
70
33
Mumbai Drive Cycle
71
34
Mumbai Drive Cycle Snapshot
71
35
Longitudinal Forces Acting on the Vehicle
73
36
Analytical Setup for Modelling the Normal Forces on Tires
77
37
Architecture of Vehicle Powertrain
78
38
Schematic of the Torque Transmission by a Single Plate Friction Clutch
80
39
Free Body Diagram of Friction Plate Clutch
81
40
Simplified Layout of Manual Transmission Unit
83
41
Macro Architecture of VESSiM
87
42
Block Diagram of Drive Control System
88
43
Functional Decomposition of Drive Control System
88
44
Architecture of the Vehicle Plant Model
89
45
Functional Decomposition of Engine Subsystem
89
46
Functional Decomposition of Clutch Subsystem
90
47
5 Speed Synchromesh Manual Transmission Unit
91
48
Functional Decomposition of the Manual Transmission Unit
91
49
Functional Decomposition of the Differential
91
50
Functional Decomposition of Vehicle Body
92
51
Functional Decomposition of the Electrical System
93
52
Details of the Engine Model Implemented
95
53
Properties of Engine Block – Torque
96
54
Properties of Engine Block – Dynamics
97
55
Properties of Engine Block – Engine Speed Threshold
97
56
Properties of Engine Block – Fuel Consumption Specifications
98
57
Properties of Engine Block – Speed Control Specifications
98
58
Fuel Consumption Map
99
59
System Level Model of Clutch
100
60
Properties of Clutch – Dimensions
101
61
Proeprties of Clutch – Friction
102
62
Properties of Clutch – Viscous Drag
102
63
Properties of Clutch – Initial Conditions
103
64
Clutch Modulator State Control
104
65
Engaging a Gear with Synchronizer
105
66
Manual Transmission Model
106
67
Synchronizer Configuration
107
68
Gear Drive Configuration
109
69
Synchronizer Configuration – Dog Clutch
109
70
Synchronizer Configuration – Cone Clutch
110
71
Synchronizer Configuration – Detent
110
72
Synchronizer Configuration – Shift Linkages
111
73
Synchronizer Configuration – Initial Conditions
111
74
Gear Engage Feedback Logic
113
75
Differential Model
113
76
Vehicle Body Model
114
77
Vehicle Body Configuration
117
78
Tire Model Configuration – Tire Force
117
79
Tire Model Configuration – Dimensions
118
80
Tire Model Configuration – Dynamics
118
81
Tire Model Configuration – Rolling Resistance
118
82
Tire Model Configuration – Slip Calculation
119
83
Brake System Model
119
84
Brake Force Distribution Model
119
85
Disc Brake Model
120
86
Electrical System Model
122
87
Alternator Model
123
88
Alternator Model Configuration
124
89
Battery
124
90
Configuration of Battery
125
91
Electrical System Actuator Control Panel
127
92
Dash Board for Data Visualization
128
93
New European Drive Cycle
130
94
Mumbai Drive Cycle
131
95
Tolerances on Vehicle Speed
132
96
Gear Shift Map
133
97
Gear Shift Schedule for 3rd Gear
133
98
Sequence of Events during a Gear Shift
134
99
Drive Control System
135
100
PID Controller for Throttle
138
101
Configuration of PID Controller for Throttle
138
102
Configuration of PID Controller for Brake
139
103
Brake Router State Machine
139
104
Transmission Control System
140
105
State Flow for Gear Shift
141
106
Response at 1st Gear 10 Km/Hr
144
2 nd
107
Response at
Gear 20 Km/Hr
145
108
Response at 3rd Gear 30 Km/Hr
145
4th
109
Response at
110
Response at 5th Gear 45 and 50 Km/Hr 5th
Gear 40 Km/Hr
111
Response at
112
Response at 5th Gear 65 ad 70 Km/Hr 5th
Gear 55 and 60 Km/Hr
145 146 146 146
113
Response at
Gear 80 Km/Hr
147
114
Response at 5th Gear 90 Km/Hr
147
115
Response at 5th Gear 100 Km/Hr
147
5th
116
Response at
Gear 110 Km/Hr
148
117
Response at 5th Gear 120 Km/Hr
148
118
Response to Braking Request from 5th Gear 120 Km/Hr to Stop
149
119
Closed Loop Controller Performance on MDC
152
120
Closed Loop Controller Performance on MDC – Peak 1
153
121
Closed Loop Controller Performance on MDC – Peak 2
153
122
Closed Loop Controller Performance on MDC – Peak 3
154
123
Closed Loop Controller Performance on MDC – Peak 4
154
124
Engine Performance
155
125
Validation of Shift Control Protocol
157
126
Validation of Shift Control Protocol – 2nd Gear Upshift and Downshift
158
127
Validation of Manual Transmission Model - 2nd Gear Upshift and Downshift
159
128
Base Load Current – Day Time Normal
160
129
Brake Lamp Current – Day Time Normal
160
130
Alternator Performance – Day Time Normal Weather Loading
161
131
Battery Charge Balance – Day Time Normal Weather
162
132
Base Electrical Load Current – Night Time Summer
163
133
Brake Lamp Current – Night Time Summer
163
134
Head Lamp Current – Night Time Summer
164
135
Blower Motor Speed and Current – Night Time Summer
164
136
Condenser/Radiator Motor Speed and Current – Night Time Summer
164
137
Alternator Performance – Night Time Summer
165
138
Battery Charge Balance – Night Time Summer
166
139
Clutch Model Performance
167
140
Clutch Model Performance – during Take Off
168
141
Clutch Model Performance – during Gear Change
168
142
Brake System Performance
170
143
Brake System Performance – Snapshot
171
144
Front Wheel Tire Slip
172
145
Horizontal Force during Acceleration
172
146
Horizontal Force during Acceleration
172
List of Tables Table #
Title
Page Number
1
Design Considerations and Parameters for the Components of Starting and Charging Systems
17
2
Design Considerations and Parameters for Starting and Charging Systems
18
3
Typical Outputs from BMS
25
4
State Transitions Control for AMS
27
5
Important Parameters of Alternator Management System
28
6
Outputs of Alternator Management System
30
7
System of Units for Reports
42
8
Accuracy Requirements
43
9
Specifications for Charge Balance Simulation
72
10
Model Blocks and Model Specifications – Engine
96
11
Engine System Signals and Data Specifications – Variables
99
12
Engine System Signals and Data Specifications – Parameters
99
13
Model Blocks and Specifications – Clutch
101
14
Clutch System Signals and Data Specifications – Variables
103
15
Important Model Blocks and Specifications – Simple Gear
108
16
Important Model Blocks and Specifications – Synchronizer
108
17
Transmission System Signal and Data Specifications – Variables
112
18
Transmission System Signal and Data Specifications – Parameters
112
19
Differential System Signal and Data Specifications – Variables
113
20
Differential System Signal and Data Specifications – Parameters
113
21
Vehicle Body System Signal and Data Specifications – Variables
115
22
Vehicle Body System Signal and Data Specifications – Parameters
115
23
Important Model Blocks and Specifications – Vehicle Body
116
24
Important Model Blocks and Specifications – Tire
116
25
Brake System Signal and Data Specifications – Variables
121
26
Brake System Signal and Data Specifications – Parameters
121
27
Alternator Signal and Data Specifications – Variables
124
28
Alternator Signal and Data Specifications – Parameters
124
29
Battery Signal and Data Specifications – Variables
126
30
Battery Signal and Data Specifications – Parameters
126
31
NEDC Specifications
131
32
MDC Specifications
131
33
Important Model Blocks and Specifications – Drive Control System
136
34
Drive Control System Signal and Data Specifications – Variables
137
35
Drive Control System Signal and Data Specifications – Parameters
137
List of Figures Figure #
Title
Page Number
1
Process of Mathematical Modelling
2
2
Mass and Damper System
2
3
Mass with Spring and Damper Modelled in Simulink®
4
4
Deployment in Simscape®
5
5
Model Response
5
6
Illustration of Hierarchical System
6
7
Classification of Systems
7
8
Systems Engineering Model
8
9
Timeline of Implementation of Emission Norms
10
10
Solutions Implemented for Emission Control
11
11
Topology of Vehicle Electrical System
12
12
Exploded View of a Typical Automotive Alternator
12
13
AC Output from Stator
13
14
Rectified DC Output
13
15
Schematic of the Alternator
14
16
Construction of an Automotive Battery
15
17
Construction of an Automotive Starter Motor
16
18
Micro Hybrid System Architecture
19
19
Intelligent Battery Sensor
20
20
ESS System Function
22
21
ESS System Functional Behavior
22
22
Architecture of Micro Hybrid Control System
24
23
State Control Machine for AMS
26
24
Comparison of Battery Terminal Voltages
27
25
Effect of Battery State of Charge
28
26
Comparison of Charge Balance
31
27
Fuel Economy Improvement due to Intelligent Alternator Control System and Other Functions of Micro Hybrid System
31
28
Energy Recuperation Trend in a Micro Hybrid
32
29
Systems Engineering Model of MHS Development
34
30
Effort V/S Project Schedule
35
31
Test Input for Analyzing the Controller Response during Acceleration
70
32
Test Input for Analyzing the Controller Response during Deceleration
70
33
Mumbai Drive Cycle
71
34
Mumbai Drive Cycle Snapshot
71
35
Longitudinal Forces Acting on the Vehicle
73
36
Analytical Setup for Modelling the Normal Forces on Tires
77
37
Architecture of Vehicle Powertrain
78
38
Schematic of the Torque Transmission by a Single Plate Friction Clutch
80
39
Free Body Diagram of Friction Plate Clutch
81
40
Simplified Layout of Manual Transmission Unit
83
41
Macro Architecture of VESSiM
87
42
Block Diagram of Drive Control System
88
43
Functional Decomposition of Drive Control System
88
44
Architecture of the Vehicle Plant Model
89
45
Functional Decomposition of Engine Subsystem
89
46
Functional Decomposition of Clutch Subsystem
90
47
5 Speed Synchromesh Manual Transmission Unit
91
48
Functional Decomposition of the Manual Transmission Unit
91
49
Functional Decomposition of the Differential
91
50
Functional Decomposition of Vehicle Body
92
51
Functional Decomposition of the Electrical System
93
52
Details of the Engine Model Implemented
95
53
Properties of Engine Block – Torque
96
54
Properties of Engine Block – Dynamics
97
55
Properties of Engine Block – Engine Speed Threshold
97
56
Properties of Engine Block – Fuel Consumption Specifications
98
57
Properties of Engine Block – Speed Control Specifications
98
58
Fuel Consumption Map
99
59
System Level Model of Clutch
100
60
Properties of Clutch – Dimensions
101
61
Proeprties of Clutch – Friction
102
62
Properties of Clutch – Viscous Drag
102
63
Properties of Clutch – Initial Conditions
103
64
Clutch Modulator State Control
104
65
Engaging a Gear with Synchronizer
105
66
Manual Transmission Model
106
67
Synchronizer Configuration
107
68
Gear Drive Configuration
109
69
Synchronizer Configuration – Dog Clutch
109
70
Synchronizer Configuration – Cone Clutch
110
71
Synchronizer Configuration – Detent
110
72
Synchronizer Configuration – Shift Linkages
111
73
Synchronizer Configuration – Initial Conditions
111
74
Gear Engage Feedback Logic
113
75
Differential Model
113
76
Vehicle Body Model
114
77
Vehicle Body Configuration
117
78
Tire Model Configuration – Tire Force
117
79
Tire Model Configuration – Dimensions
118
80
Tire Model Configuration – Dynamics
118
81
Tire Model Configuration – Rolling Resistance
118
82
Tire Model Configuration – Slip Calculation
119
83
Brake System Model
119
84
Brake Force Distribution Model
119
85
Disc Brake Model
120
86
Electrical System Model
122
87
Alternator Model
123
88
Alternator Model Configuration
124
89
Battery
124
90
Configuration of Battery
125
91
Electrical System Actuator Control Panel
127
92
Dash Board for Data Visualization
128
93
New European Drive Cycle
130
94
Mumbai Drive Cycle
131
95
Tolerances on Vehicle Speed
132
96
Gear Shift Map
133 3rd
97
Gear Shift Schedule for
98
Sequence of Events during a Gear Shift
Gear
133 134
99
Drive Control System
135
100
PID Controller for Throttle
138
101
Configuration of PID Controller for Throttle
138
102
Configuration of PID Controller for Brake
139
103
Brake Router State Machine
139
104
Transmission Control System
140
105
State Flow for Gear Shift
141
106
Response at 1st Gear 10 Km/Hr
144
107
Response at 2 nd Gear 20 Km/Hr
145
3rd
108
Response at
Gear 30 Km/Hr
145
109
Response at 4th Gear 40 Km/Hr
145
5th
110
Response at
Gear 45 and 50 Km/Hr
146
111
Response at 5th Gear 55 and 60 Km/Hr
146
5th
112
Response at
113
Response at 5th Gear 80 Km/Hr 5th
Gear 65 ad 70 Km/Hr
147
114
Response at
115
Response at 5th Gear 100 Km/Hr
147
116
Response at 5th Gear 110 Km/Hr
148
5th
Gear 90 Km/Hr
146
Gear 120 Km/Hr
147
117
Response at
118
Response to Braking Request from 5th Gear 120 Km/Hr to Stop
148 149
119
Closed Loop Controller Performance on MDC
152
120
Closed Loop Controller Performance on MDC – Peak 1
153
121
Closed Loop Controller Performance on MDC – Peak 2
153
122
Closed Loop Controller Performance on MDC – Peak 3
154
123
Closed Loop Controller Performance on MDC – Peak 4
154
124
Engine Performance
155
125
Validation of Shift Control Protocol
157
126
Validation of Shift Control Protocol – 2nd Gear Upshift and Downshift
158
127
Validation of Manual Transmission Model - 2nd Gear Upshift and Downshift
159
128
Base Load Current – Day Time Normal
160
129
Brake Lamp Current – Day Time Normal
160
130
Alternator Performance – Day Time Normal Weather Loading
161
131
Battery Charge Balance – Day Time Normal Weather
162
132
Base Electrical Load Current – Night Time Summer
163
133
Brake Lamp Current – Night Time Summer
163
134
Head Lamp Current – Night Time Summer
164
135
Blower Motor Speed and Current – Night Time Summer
164
136
Condenser/Radiator Motor Speed and Current – Night Time Summer
164
137
Alternator Performance – Night Time Summer
165
138
Battery Charge Balance – Night Time Summer
166
139
Clutch Model Performance
167
140
Clutch Model Performance – during Take Off
168
141
Clutch Model Performance – during Gear Change
168
142
Brake System Performance
170
143
Brake System Performance – Snapshot
171
144
Front Wheel Tire Slip
172
145
Horizontal Force during Acceleration
172
146
Horizontal Force during Acceleration
172
List of Tables Table #
Title
Page Number
1
Design Considerations and Parameters for the Components of Starting and Charging Systems
17
2
Design Considerations and Parameters for Starting and Charging Systems
18
3
Typical Outputs from BMS
25
4
State Transitions Control for AMS
27
5
Important Parameters of Alternator Management System
28
6
Outputs of Alternator Management System
30
7
System of Units for Reports
42
8
Accuracy Requirements
43
9
Specifications for Charge Balance Simulation
72
10
Model Blocks and Model Specifications – Engine
96
11
Engine System Signals and Data Specifications – Variables
99
12
Engine System Signals and Data Specifications – Parameters
99
13
Model Blocks and Specifications – Clutch
101
14
Clutch System Signals and Data Specifications – Variables
103
15
Important Model Blocks and Specifications – Simple Gear
108
16
Important Model Blocks and Specifications – Synchronizer
108
17
Transmission System Signal and Data Specifications – Variables
112
18
Transmission System Signal and Data Specifications – Parameters
112
19
Differential System Signal and Data Specifications – Variables
113
20
Differential System Signal and Data Specifications – Parameters
113
21
Vehicle Body System Signal and Data Specifications – Variables
115
22
Vehicle Body System Signal and Data Specifications – Parameters
115
23
Important Model Blocks and Specifications – Vehicle Body
116
24
Important Model Blocks and Specifications – Tire
116
25
Brake System Signal and Data Specifications – Variables
121
26
Brake System Signal and Data Specifications – Parameters
121
27
Alternator Signal and Data Specifications – Variables
124
28
Alternator Signal and Data Specifications – Parameters
124
29
Battery Signal and Data Specifications – Variables
126
30
Battery Signal and Data Specifications – Parameters
126
31
NEDC Specifications
131
32
MDC Specifications
131
33
Important Model Blocks and Specifications – Drive Control System
136
34
Drive Control System Signal and Data Specifications – Variables
137
35
Drive Control System Signal and Data Specifications – Parameters
137
VESSiM
Introduction
1 Introduction Mathematical Modelling and Simulation is widely deployed during the development of most of the products since last few years. Particularly in complex products like a vehicle, be it a commercial vehicle or a passenger vehicle, mathematical modelling and simulation is proving to be highly productive, as it enables the engineers to gain an advanced insight into the product or system under development. Various commercial tools are available for this purpose, and some of them even provide turnkey solutions various problems. Hermann Schichl, in [1.1] describes that the etymology of the word “Modelling” has its roots in the Latin word modellus. Further, it is elaborated that abstract form of modelling was even witnessed in the Stone Age, and conceptualizing an abstract models was the unique ability which gave an edge to the species of Homo Sapiens (of which we are the descendants) an edge over other less developed human races like Homo Neanderthals. Further, before defining the word model, Hermann Schichl, has provided a good insight into the history of modelling in [1.1].
1.1
Mathematical Modelling
Generally, a model is a simplified version of what is real or something under study. For example, before the construction of a large building, its scaled down model is constructed to study various aspects of the building and its construction process. Then, the scientific definition of a mathematical model is the abstraction of a system or a practical problem in terms of formalized mathematical language. Mathematical language is the language of equations and numbers, and numbers often being expressed as symbols. The equations are always under equilibrium or treated as under equilibrium. Consider, the following equation as an example of a mathematical model – y = ax + b In this model or equation, we have following entities – Variables – As we know terms y and x are known as variables, as their values or properties keep changing either with respect to time, or with respect to each other. In any mathematical model, there are known variables (Independent Variables), whose value is known to us, and there are unknown variables (Dependent Variables), which are to be found out from the mathematical model. Relations – The entire equation is the relation between the known and unknown variables in the mathematical model. AETT ZG 629T
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Data – Data term is the constants or parameters which support the mathematical model. For instance, the constants a and b in the considered example are Data. Therefore, any number in the model, which is not a variable, but is required for the relation or equation to be fulfilled is Data.
1.2
Modelling Process and Simulation
Hermann Schichl, provides and abstract form of modelling process in [1.1], which is reproduced as shown in Figure 1.
Figure 1 – Process of Mathematical Modelling Thus, the mathematical modelling is an iterative process, involving five distinct phases. The practical problem is first studied, and a concept or prototype model is them constructed. This is also known as architectural modelling, in which the constants or parameters are not known or not estimated. Known and unknown variables are established. Then, required data is collected by studying the problem, typically through experimental investigations. The model is then solved to find out the solution, and model results are interpreted and analysed. The results are compared to actual physical behaviour of the problem and the process is revisited if it is necessary to tune or correct the model. Let us consider the simple example of a mass and damper system as shown in Figure 2.
Figure 2 – Mass and Damper System AETT ZG 629T
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The process of modelling this practical problem is demonstrated through following sections – Step 1 – Studying the Practical or Real World Problem In this step, various elements of the system are deconstructed in terms of corresponding mathematical terms. In the considered example of mass attached to a spring and damper, various elements are the mass, damper, spring, and the excitation force. Each element is given a mathematical symbol for its expression in the model. Correspondingly, let – M = Mass of the System in Kg k = Stiffness of the Spring in N/m c = Damping Co-efficient in N-s/m F = Excitation Force in N Among the above, as evident already, the mass, stiffness, and the damping coefficient are the data or the constants. Excitation force is independent variable. Let us then consider the position of the mass and its velocity be the unknown variables which need to be found out. Thus, denoting that – x = Position of the Mass in meters. 𝑥𝑥̇ = Velocity in m/s.
𝑥𝑥̈ = Acceleration of the Mass in m/s2.
Step 2 – Formulation of the Mathematical Model In this step, we need to identify the equation of motion for the considered system, which is often known as the governing equation. Mathematical Model is derived by resolving the dependent variables to independent variables, through the application of fundamental laws. In the considered example, we can apply the Newton’s Second Law of Motion and we obtain the model as -
Step 3 – Data Collection
𝑀𝑀𝑥𝑥̈ + 𝑐𝑐𝑥𝑥̇ + 𝑘𝑘𝑘𝑘 = 𝐹𝐹(𝑡𝑡)
(1.1)
This step is also known as Parameter Identification, as the data or parameters or constants are identified in this step. In addition, the solution required or the unknown variable to be solved is also identified. Let us consider, the system data as follows – M = 100 Kg k = 1000 N/m c = 0.1 N-s/m
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F = 500 N, applied suddenly, from initial 0 N. Step 4 – Computing the Solution or Simulation Once the parameters have been identified, the next step is to deploy the parameter values and solve the governing equation. Before the solution, the governing equation must be simplified, in order to reduce the effort required to solve the problem. Equation 1, for the considered example can be simplified as –
𝑥𝑥̈ =
1
𝑀𝑀
[𝐹𝐹 (𝑡𝑡) − 𝑐𝑐𝑥𝑥̇ (𝑡𝑡) − 𝑘𝑘𝑘𝑘]
(1.2)
If the excitation force is time varying, equation 2 needs to be solved progressively over the time, and the values of 𝑥𝑥̈ must be integrated to get the velocity and displacement. Commercially available tools like
Simulink® and Simscape® in Matlab®, help us to formulate the model and also solve the problem. Figure 3 shows the deployment of equation 2 in Simulink® model.
Figure 3 – Mass with Spring and Damper modelled in Simulink® Some advanced tools like Simscape® help us to model the system graphically, without modelling the governing equations. Figure 4 shows the deployment of the considered system in Simscape® environment. As evident from Figure 4, the example is deployed, in a simple graphical form, and the mathematical expression is hidden below the deployment. This approach is termed as “Physical Systems” modelling, in which the physical topology of the system is modelled, without going into the mathematical expressions involved. Although, the solution to the problem is solved mathematically, which involves the steps like converting the physical model into the mathematical model, and solving it, such tasks are handled by the tool. Thus, the modelling process is simplified and modelling is more robust. Such an approach eliminates the chances of error while deploying the equations, while developing the model. Therefore, the results of the solution are always reliable and are far more accurate than the previous approach. More about the advantages of physical system modelling is discussed in the later sections. Figure 5 shows the response of the system modelled, for an excitation force of 500 N, applied as a function of time.
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Figure 4 – Deployment in Simscape®
Figure 5 – Model Response
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1.3
Introduction
Systems Engineering
Systems Engineering approach was deployed in this project. Therefore, a brief discussion is held in the following sections on the topic of Systems Engineering.
1.3.1 System There are many definitions of System, based on the application or the domain of study. Some of the standardized definitions accepted by the industries are as follows – As per ISO/IEC 15288:2008 [3.1], a system is defined as “A set or arrangement of elements and processes that are related and whose behaviour satisfies customer/operational needs and provides for life cycle sustainment of the products.” A more detailed definition of system is provided by INCOSE Systems Engineering Handbook [1.2], which states that “A system is a construct or collection of different elements that together produce results not obtainable by the elements alone. The elements, or parts, can include people, hardware, software, facilities, policies, and documents; that is, all things required to produce systems-level results. The results include system level qualities, properties, characteristics, functions, behaviour and performance. The value added by the system as a whole, beyond that contributed independently by the parts, is primarily created by the relationship among the parts; that is, how they are interconnected.” Therefore, for a domain to be recognized as a system, more than one elements (parts or components) must be connected together, such that they interact to deliver some output, and more importantly an output with a purpose. Thus, it becomes very easy to realize that we are always surrounded by the systems. Right from our own human body to every useful thing we use today, like a passenger car is a system. However, things get complicated when we start discovering systems around us, and find that the elements within a system, the components, are not single entities and are systems in themselves. For example, in a passenger car, an engine is a system in itself. Therefore, another term is introduced here as “sub-system”, which is a system in itself by definition, but is a constituent of a larger system performing the main function. In addition, some more terms which are of importance are “Major Sub-Systems” and “Minor Sub-Systems”, which can help is segmenting the a given system in a hierarchy, as shown in figure 6.
Figure 6 – Illustration of a Hierarchical System AETT ZG 629T
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1.3.2 Classification of Systems Figure 7 illustrates a relevant classification of a system for this project.
Figure 7 – Classification of Systems
1.3.3 Systems Engineering Systems Engineering, in simple words is the interdisciplinary field, dealing with the process of designing complex systems over their life cycles. A complex product like a passenger car contains many sub-systems which are interdisciplinary, as shown in figure 6. Systems engineering is thus the part of the vehicle development, which overlaps over the design and development of each of such sub-systems, dealing with issues like how the constituent sub-systems will interact with each other or are connected with each other to achieve the desired larger purpose. Therefore, a systems engineer must work and solve problems which are spread across two or more domains of engineering.
1.3.4 Systems Engineering Process / Model In order to streamline and consolidate the interdisciplinary work, a standard approach is thus deployed globally. This approach is known Systems Engineering Model or more generally the “V” model, due to the graphical representation of the model, which is shown in figure 8. Figure 8 illustrates the systems engineering model deployed for the development of VESSiM specifically. Included phases are discussed in detail in the relevant chapters.
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Figure 8 – Systems Engineering Model
1.4
System Modelling
Systems Engineering approach encourages the tools which help to understand the complicated systems through an approach known as “Model Based Design”, in which the mathematical model of the system (components connected with each other in such a way that they simulate or mimic the system function) is the preliminary step. Thus, in Systems Engineering approach, the term mathematical modelling is often interchanged with System Modelling. However, the system models can be of two types, as discussed below.
1.4.1 Mathematical Model A pure mathematical model of a system is simply a mathematical equation representing the system behaviour. For example, the model expressed by equations 1 and 2, and modelled as shown in figure 3.
1.4.2 Physical Model Physical modelling does not involve the identification of the mathematical model representing the system or problem domain. Usually, a physical model can be developed using certain commercial tools like Simscape, (for example the model shown in figure 4), in which the model is represented by “elements”, which are connected with each other, representing the physical topology of the system. Underlying mathematical expressions are hidden from the end user. While solving the problem, the tool converts the physical model into the mathematical model in the background and provides the solution. Therefore, the physical system modelling has an edge over the mathematical modelling, due to following features – 1.
Complexities of the detailed mathematical modelling are avoided.
2.
Physical modelling tools make it a lot easier to develop the physical model with the readily usable block sets which emulate the performance of the components or subsystems, with their associated parameters.
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Introduction
Physical modelling tools provide the parameters of the elements of the system readily, and hence the parameter identification for component or subsystem modelling is not required.
4.
Coupled systems or interdisciplinary interaction (For example heat generated by a resistor) within a system is easier to simulate, as the coupling equations need not be written.
5.
As a result of these advantages, the physical models are more robust at the effort which they take to develop.
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Advances in Vehicle Electrical Systems
Advances in Vehicle Electrical Systems
2.1 Background Automotive industry is continuously facing the challenges of greenhouse gas emission control and reduction in fuel consumption. From the earlier days, in which the vehicles were designed for purely for performance attributes like acceleration, top speed, etc. new attributes like emission limits and fuel efficiency have taken equal importance in last decade. This is necessitated by the imposition of stringent emission norms, and rising costs of gasoline and diesel. Particularly in Indian automotive market, fuel efficiency is a significant parameter one considers before buying a car, and if not more, it is as important as other features in the vehicle. Figure 9 shows the timeline of emission norms imposed in European Union (EU Norms) and trend of equivalent Bharat Stage emission norms in Indian market.
Figure 9 – Timeline of Implementation of Emission Norms Bharat Stage Emission Norms are basically derived from European Union Norms. While the norms got stricter in European Union since 1992, with the implementation of Euro 1 norms, in India, the equivalent BS 1 norms were implemented only in the year 2000. This delay was due to the technology availability in the Indian market, at the pressure of costs which is yet another significant parameter in India. The current enforced norms are BS 4 (In metro cities), and BS 3 (rest of India). By the year 2017, BS4 will be enforced across India, and in the year of 2020, BS6 which is equivalent to Euro 6 will be enforced [4.1]. Notable point is that BS5/Euro5 will not be implemented as an intermediate step.
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As evident from Figure 9, the norms are getting stricter in terms of allowable limits of toxic gasses. Carbon Monoxide which is the most important polluting gas, has seen a reduction target of close to 37% over two decades, in terms of grams per kilometre. There were no regulations imposed on unburnt hydrocarbons and particulate matters until the enforcement of Euro 3. Since Euro 3, the reduction target for these two pollutants has been 84% and 40% respectively. Another aspect of this scenario is far grimmer for conventional IC Engine powered vehicles. None of these emissions norms impose any regulations on Carbon Dioxide emissions, which calls for replacement of fossil fuels with alternative fuels and/or alternative energy sources. Electric vehicles are thus the future of mobility. However, in the medium term the IC engines are going to stay and in order to achieve targets set by regulations, significant research is undertaken. Such a complex problem is as usually dealt with a multipronged strategy. The problem becomes even more complicated as there is no single solution available to address the different pollutants. Figure 10 illustrates the strategies implemented to tackle the targets imposed on different pollutants from an IC Engine.
Figure 10 – Solutions Implemented for Emission Control A straight solution to reduce the emissions, is to reduce the fuel consumption by the engine. However, when engines are designed from fuel efficiency attribute, performance of vehicle gets affected. Therefore, the promising solution must reconcile the opposite relation between the fuel efficiency and performance. As a result, in addition to the measures shown in Figure 10, two more solutions have emerged to address the problem. One among these is the light-weighting, where in the high strength and alternative lightweight materials are being implemented to reduce the weight the vehicles. A reduction in the weight of the vehicle will always reduce the fuel consumption, and cumulatively addresses the reduction of emissions. Another important solution is the Energy Management Systems (EMS), which are aimed at optimizing the energy consumption to reduce the fuel consumption. Mostly, the EMS is centred around the electrification of the major accessory loads like steering systems and cooling systems, and more importantly systems like Micro and Mild Hybrid systems, which concentrate on preventing wasteful running of the engine and optimization of electrical energy generation, distribution, storage and consumption. In this chapter, a
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detailed discussion is held on the topic of Energy Management Systems, as the project work is centred on vehicles with such functions.
2.2 Conventional 12 Volt Automotive Electrical System
Figure 11 – Topology of Vehicle Electrical System Figure 11 shows a simplified schematic of a conventional 12 V automotive electrical system. Like any power systems, we have 4 major components or subsystems in a vehicle electrical system, which are discussed in brief in the following sections.
2.2.1 Alternator/Generator Alternator, also called as Generator, generates the electrical energy in the vehicle. It is driven by the engine through a belt drive, and converts the mechanical energy into the electrical energy. Fundamentally, an Alternator is a 3 phase AC Generator. Construction of the alternator is shown in Figure 12.
Figure 12 – Exploded View of a Typical Automotive Alternator 2.2.1.1 Construction and Working of an Alternator A typical automotive alternator consists of a strong housing which houses the entire assembly. The Rotor consists of a coil of wire wrapped around an iron core. Current through the wire coil - called "field" current - produces a magnetic field around the core. The strength of the field current determines the strength of the magnetic field. The field current is D/C, or direct current. In other words, the current flows in one direction only, and is supplied to the wire coil by a set of brushes and slip rings. The magnetic field produced has,
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as any magnet, a north and a south pole. The rotor is driven by the alternator pulley, rotating as the engine runs, hence the name "rotor." Surrounding the rotor is another set of coils, three in number, called the stator. The stator is fixed to the shell of the alternator, and does not turn. As the rotor turns within the stator windings, the magnetic field of the rotor sweeps through the stator windings, producing an electrical current in the windings. Because of the rotation of the rotor, an alternating current is produced. As, for example, the north pole of the magnetic field approaches one of the stator windings, there is little coupling taking place, and a weak current is produced, As the rotation continues, the magnetic field moves to the centre of the winding, where maximum coupling takes place, and the induced current is at its peak. As the rotation continues to the point that the magnetic field is leaving the stator winding, the induced current is small. By this time, the South Pole is approaching the winding, producing a weak current in the opposite direction. As this continues, the current produced in each winding plotted against the angle of rotation of the rotor has the form shown in Figure 13. The three stator windings are spaced inside the alternator 120 degrees apart, producing three separate sets, or "phases," of output voltages, spaced 120 degrees apart, as shown in Figure 13.
Figure 13 – AC Output from Stator
Figure 14 – Rectified DC Output
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This 3 phase AC output is then converted into a DC current output, by implementing a rectifier network, as shown in Figure 15, which shows a generalized schematic of the alternator. Figure 14 shows the waveform of the DC output from the Alternator, after the rectification.
Figure 15 – Schematic of the Alternator 2.2.1.2 Alternator Control / Regulation Alternator output voltage, thus depends on the input shaft speed and the excitation current in the rotor. In system like vehicle, the input speed to the alternator can never be constant over a period of time, as the driver commands the vehicle to move at different speeds and the correspondingly the engine speed keeps changing. Therefore, the alternator output voltage is controlled or regulated by controlling the excitation current to the rotor. This is performed by the Regulator. As shown in Figure 15, the regulator has two inputs and one output. The inputs are the field current supply and the control voltage input, and the output is the field current to the rotor. The regulator uses the control voltage input to control the amount of field current input that is allow to pass through to the rotor winding. If the battery voltage drops below the set point to be maintained, the regulator senses this, by means of the connection to the battery, and allows more of the field current input to reach the rotor, which increases the magnetic field strength, which ultimately increases the voltage output of the alternator. Conversely, if the battery voltage increases beyond the set point, regulator limits the field current through the rotor windings, and the output voltage is controlled to the level required. Initially, when the engine is not running, the regulator provides the field current to rotor, by drawing the same from the battery. When the engine starts running, a part of the alternator output current is used for providing the field current. This is called as selfexcitation. 2.2.1.3 Load Response Control (LRC) Another important aspect of the automotive alternator control is the load response control. At low engine speeds, or idling, the engine torque output is very minimum, and hence the load on the engine must be optimized. Even the vehicle creeping from stopped condition, the load on the engine must act gradually,
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otherwise the engine would stall. In such a situation, in order to minimise the load on the engine, alternator is shut down for a temporary duration, till the engine speed reaches certain predefined limit. This is called as Load Response Control (LRC) with respect to speed. The speed at which the Alternator starts producing the output is known as “Cut in Speed”. Another aspect of the LRC, is the rate at which the alternator output is increased to the required limit from zero output. If the output is raised suddenly, the delta load acting on the engine will be sudden, which leads a fluctuation of the engine speed. Thus the output voltage is gradually ramped up to the required limit. This is the time aspect of LRC. Further, the loads in the vehicle – like head lamps, blowers, etc. – can be turned on based on the driver or passenger demand. Whenever such a load is turned on, the alternator output voltage dips momentarily and then is built up again. Under such scenarios as well, the LRC is implemented. Typical time through which the output is controlled is around 200 to 500 milliseconds.
2.2.2 Battery Battery is the energy reserve in the automotive electrical system. As we know the battery stores the electrical energy in the form of chemical energy and releases it when required. Typically 12 V, Lead Acid batteries are used in automotive application, and specifically for automotive application they are known as Starter, Lighting and Ignition (SLI) batteries. Role of the battery in the automotive application is thus – •
Store the electrical energy,
•
Provide the energy required for starting the engine,
•
Balance the grid in case the load demand increases beyond the alternator capacity.
Figure 16 illustrates the internal construction of the battery.
Figure 16 – Construction of an Automotive Battery
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2.2.3 Starter Motor Starter Motor is an electric motor used for starting or cranking the engine. Though it is simply a motor, its construction is a bit complicated like a switch gear, due to the inclusion of a solenoid which engages the starter motor with the engine flywheel ring gear. Figure 17 shows the construction of an automotive starter motor. The starter motor is mounted on the engine, such that a pinion gear mounted on the rotor can be engaged with the ring gear on the flywheel of the engine. The engagement is achieved by a solenoid. When the key input is given to the solenoid, it pushes the pinion gear towards the flywheel. On the way it switches the power supply to motor through internal connections and motor starts to rotate freely, as the pinion is not yet engaged with the ring gear. When the pinion is engaged with the ring gear, the solenoid turns on the high current path for the motor and motor starts driving the flywheel. When the engine is started, and the key input is withdrawn the solenoid withdraws the pinion gear and disconnects the power supply to motor. An overrunning clutch or one way clutch is implemented in the motor to ensure that the flywheel will not drive the motor when the engine speed increases in the process of starting.
Figure 17 – Construction of an Automotive Starter Motor
2.2.4 Loads Loads are the consumers of the electrical energy in the vehicle electrical system. Starter motor itself is a primary load. Further, all the electrical devices like head lamps, blowers, fan motors, sensors, actuators, and control units are considered as loads.
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2.2.5 Starting and Charging System Starting system is thus the system consisting of the start motor, battery and the electrical circuit along with the ignition switch. Similarly, the charging system is alternator and battery together with the associated circuit components.
2.2.6 Important Design Considerations for Components of Starting and Charging System Table 1 – Design Considerations and Parameters for the Components of Starting and Charging Systems
Sl.#
Parameter
Requirement
Influence
Alternator 1
Peak Current Output (Amperes)
Peak current output of the
Influences the charging of
alternator must be such that it
the battery negatively if
can deliver the required
the capacity is selected is
current demand to all the
lower.
loads of the vehicle. 2
Part Load Characteristics
Part load characteristics must
Influences the charging of
Alternator characteristics of Current
be such that the alternator
the battery negatively if
Output V/S Voltage V/S Speed V/S
provides enough current
the capacity is selected is
under part load, which is
lower.
Temperature
medium engine speed. 3
4
Inertia
Belt Drive Pulley Ratio
Weight must be lower to
Influences
power
to
increase efficiency.
weight ratio.
Must be optimized for speed
Higher ratios can reduce
input to alternator.
the output at low rotor speeds.
Battery 1
C20/C5 Rated Capacity (AHr)
Must be selected
Defines total on-board
Duration for which the battery can
appropriately based on the
electrical energy stored.
continuously
load ratings and weight
provide
C20/C5
rated
current, without reaching the discharge
requirements.
voltage limit.
2
CCA (Amperes)
Must be higher than the
Starting performance of
Cold Cranking Amperes – Current output
current demand by the motor
the vehicle under cold
capacity of the battery to provide high
at specified sub-zero
ambient
temperature, to crank the
(Cold Cranking).
temperatures.
amount of current at a specified sub-zero temperature, continuously for 30 seconds
engine.
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Reserve Capacity (Minutes)
Must be selected
This parameter signifies
Duration for which the battery can
appropriately, based on the
the duration for which the
provide 25 Amperes of constant current
vehicle electrical system
battery can support the
performance attribute.
vehicle electrical system,
discharge,
without
reaching
the
discharge voltage limit.
in case of an alternator failure. 4
Charge Acceptance (Amperes) Charging Current accepted at
Must be as high as possible.
10th
Influences the charging duration of the battery,
minute during a constant voltage charge,
and
fuel
economy
at specified temperature
indirectly. Starter Motor 1
Cranking Speed (RPM)
Must be selected based on the
Lower
engine starting speed.
will
starting increase
speeds starting
duration. 2
Torque Output
Must be enough to crank the
Influences
engine from stalled condition,
requirement
at a specified sub-zero
battery.
the
CCA
of
the
temperature. Depends on Engine Inertia, Compression Ratio, and Fuelling Strategy.
2.2.7 System Level Performance Requirements Table 2 – Design Considerations and Parameters for Starting and Charging Systems
Sl.#
Parameter
Requirement Starting System
1
•
Cranking Performance Ability to crank the engine in a range of
be selected such that it can crank the engine in the
operating temperatures as defined in the Vehicle Technical Specifications
Starter Motor Cranking Speed and Torque output must
worst case of Engine Drag Torque. •
Battery CCA must be selected such that it supports the peak current requirement of the motor in the same condition of worst case drag torque.
•
Cables between Starter Motor and Battery must be designed such that the voltage drop due to the resistance of the cable is minimum (as specified by every OEM’s internal standard).
Charging System 1
Charge Balance
•
Typically a drive cycle which has higher idling period is selected for the charge balance test.
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Cumulative energy stored in the battery
•
when the vehicle is driven on chassis
Vehicle is driven on the chassis dynamometer, under specified environmental conditions and load duty cycle,
dynamometer, following the specified
typically for one hour.
drive cycle, and with the specified load duty
cycle
and
environmental
conditions.
•
At the end of the test, the battery State of Charge (Ratio of Available Capacity to Maximum Capacity), must
NOTE: This test is discussed in detail in the following one of the chapters.
increase by a specified margin.
2.3 Micro Hybrid Systems (MHS) Micro Hybrid Systems is another term by which the Vehicular Energy Management Systems are popularly known. As discussed in brief earlier, MHS is targeted at reducing the fuel consumption of the engine, and thus cumulatively reduces the emission of pollutant and toxic gasses. Fundamentally, a MHS is a conventional IC Engine powered vehicle, with a 12V electrical system, in which some of the functions of Hybrid Electric Vehicles (HEV) are implemented. The difference between a HEV and a vehicle with MHS is that the amount of on-board electrical energy is lesser in a vehicle with MHS, and thus the vehicle is not propelled by the electrical energy. There is an intermediate Mild Hybrid System, in which we have a 42 or 48 V electrical system, with and Integrated Starter and Alternator, which can provide additional torque boost (active) to the engine output during acceleration. However, the functions implemented in Mild and Micro Hybrid Systems are similar, though they are realized and controlled in different methods.
2.3.1 System Architecture
Figure 18. Micro Hybrid System Architecture Figure 18 shows the logical block diagram of the MHS. The control system or control algorithms of the IAC are implemented in the Engine Management System (EMS) ECU. The other two important components of the MHS are the Intelligent Battery Sensor (IBS) and Intelligent Alternator (IAL). For the Engine Stop/Start, the starter motor is controlled through the conventional method of actuation by relays. EMS also receives other signals like Accelerator Pedal Position, Clutch Pedal Position, Brake Pedal Switch, etc. either through hardwired inputs or over the Controller Area Network (CAN). EMS receives the battery
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status from the IBS on the Local Interconnect Network (LIN), which is a single wire communication protocol suitable for the low speed and low data transfer.
2.3.2 Components of the Micro Hybrid System 2.3.2.1 Intelligent Battery Sensor (IBS) The Intelligent Battery Sensor is mounted on the battery negative terminal with its clamp. The vehicle’s main negative cable is routed through the shunt of IBS, for measuring the current flowing in and out of the battery. An electronic module is the core of the IBS which performs the measurements and estimations on the battery. IBS communicates the battery data on a communication line to the micro hybrid controller. Widely used communication protocol is Local Interconnect Network (LIN) as the amount of data and transfer speed requirements are low, and it offers a much simpler communication on a single wire, with a master and slave architecture. The role of the IBS in micro hybrid systems is discussed in details in [2.2] and [2.3]. The IBS performs three direct measurements, Battery Voltage, Battery Current and Battery Temperature. These values are then used in the IBS framework software, which essentially uses a mathematical model of the installed battery to estimate the battery parameters like Battery State of Charge (SOC), State of Function (SOF), State of Health (SOH). In addition mission critical diagnostic checks on the battery like Weak Cell Detection, Wrong Battery Installation, etc. are also performed.
Figure 19. Intelligent Battery Sensor 2.3.2.2 Intelligent Alternator (IAL) The Intelligent Alternator (also known as Smart Alternator), in terms of physical construction, is same as any conventional alternator. The difference is observed in the Regulator. The Regulator of an IAL, though electrically and physically same as shown discussed earlier, does not control the alternator by itself. It simply obeys the commands issued by the EMS ECU. That is the control methods which were inbuilt to the regulator are transferred to an external Master. Therefore, word Intelligent Alternator is actually a misnomer, as the Regulator does not take any actions on its own, and simply executes the commands given by an external Master. It is the external control which is intelligent or smart.
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2.3.2.3 Electronic Control Unit (ECU) An Electronic Control Unit (ECU), like any automotive electronic system, is the brain of the system. However, the MHS in most of the examples, does not have a dedicated control unit. The control system program or algorithms are implemented on any of the available control units in the vehicle. Mostly, the Engine Management System (EMS) is selected, as it has the best of hardware resources on-board, among the other ECUs in a vehicle, and all the required inputs for the MHS are already available to it. 2.3.2.4 Communication System – Local Interconnect Network (LIN Bus) The LIN bus is an inexpensive serial communications protocol, which effectively supports remote application within a car’s network. It is particularly intended for mechatronic nodes in distributed automotive applications, but is equally suited to industrial applications. It is intended to complement the existing CAN network leading to hierarchical networks within cars. The LIN bus uses a master/slave approach that comprises a LIN master and one or more LIN slaves. The Master Node commands the Slave
Nodes to transmit the required message, and any node cannot broadcast a message on its own. The baud rate for the current protocol, LIN 2.3 is up to 19.2 kbps. More information about the protocol is discussed in [1.3] In the MHS, as discussed earlier, EMS ECU is the Master. IBS and IAL are slave nodes. In order to read the battery data, (for example, the battery SOC), the EMS transmits a Master Request to IBS for message which contains the required data. IBS responds to the same. The IAC control algorithm, then decides the commands to be given to IAL, and transmits the same. IAL executes the commands and provides the feedback messages to EMS. A detailed discussion on the same is held in the following sections. A detailed discussion is held in the following sections about the functions of MHS.
2.4 Engine Stop/Start System (ESS) 2.4.1 Function Explained Engine Stop/Start System in simple terms is the automation of the engine stop and restart, when the engine is running in idle conditions. For example, during a traffic signal stop, those who are conscious of the fuel economy, turn off their engines when stopping for a longer time at a traffic signal and restart the engine and take off when it’s time to move on. However, ESS is not a latest trend and attempts have been made since 1970s to have a system that shuts down the engine autonomously, when the engine is running at idle speeds, and allows the engine to be restarted easily, without the need of manual cranking. It is discussed in [2.4] about the historical aspects of ESS. Some early variants of ESS were implemented in 1980s. Further, the development of Electric Hybrid Powertrains mandated ESS, as there was a need to stop and start the engine quickly, without any manual inputs form driver. However, the momentum for ESS was generated much later, only in 2006, with the enforcement of stiff regulations for emissions and increasing fuel prices. ESS system was borrowed from hybrid powertrains
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and was implemented in conventional power trains to achieve the emission level targets. Tier 1 suppliers developed turnkey systems for quick deployment and collaborative research was carried out extensively to develop the ESS, to make it more promising, as discussed in [2.4]. Figure 20 illustrates how the ESS system works from an end user perspective. Figure 21 shows the functions of ESS for a vehicle with manual transmission, mapped from a test vehicle running on ECE 1 Drive cycle. When the control system detects that the vehicle speed is 0, it waits for the driver to shift the transmission to neutral, and then the release of clutch and brake pedals. Once this set of events is detected, the system waits till a calibrated time limit, before triggering the auto engine stop. To restart the engine, the driver has to press the clutch pedal slightly (10% of pedal travel), keeping the transmission in neutral. For an automatic transmission vehicle, the control is much easier, and auto stop/start is triggered only by the brake pedal press/release action, apart from transmission shift lever position. In this way, unnecessary idle running of the engine is prevented, contributing to improvement in fuel economy and reduction in emissions. As evident from Figure 21, the engine was stopped for a duration of approximately 30 seconds, when all the conditions for the auto engine stop were met. Therefore, the overall fuel consumption will be reduced by a proportionate amount.
Figure 20. ESS System Function
Figure 21. ESS System Functional Behaviour.
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2.4.1.1 Limitations for the Auto Stop/Start Trigger Although the control algorithm for ESS seems simple and easy, there are multiple checks on various vehicle systems, before the auto engine stop is triggered. These conditions are enforced to achieve the functional safety and ensure passenger comfort. 1.
Brake Pedal – If brake pedal is pressed, when the vehicle is stopped, auto engine stop is disabled. This is to ensure the availability of the vacuum in the Brake Booster, which requires the engine to be running for vacuum pressure availability. If the vacuum in the Brake Booster depletes, driver has to put excessive force on the brake pedal to prevent the vehicle from rolling.
2.
Vehicle Speed – Auto stop is triggered only after crossing a predefined/calibrated threshold of vehicle speed. This ensures that for short distances travelled at lower speeds, like while parking the car, auto stop is not triggered, to prevent the frustration of driver.
3.
HVAC – If the HVAC demand is high, that is if the driver has selected the blower speed more than certain predefined/calibrated level, auto stop is disabled, to ensure the comfort of passengers.
4.
Battery Status – If the battery is low on charge, auto stop is disabled, as auto start may not be possible.
5.
Electrical Load Status – If the electrical load demand is more than a predefined/calibrated limit, auto stop is disabled, as battery would deplete excessively if the engine is stopped.
6.
Doors and Hood – If any of the doors or hood is open auto start is disabled to ensure the safety of the passengers.
7.
Engine Coolant Temperature – If the engine has not warmed up fully, auto stop is disabled, as it may be difficult to restart the engine, when coolant temperature is low.
8.
System Faults – If there are any system faults like, network communication error, etc. auto stop is disabled.
Therefore, while 3 of the events can trigger an auto stop, there could be 8 or more events which can disable the auto stop/start. These aspects of ESS are discussed in details in [2.4] and [2.6].
2.5
Intelligent Alternator Control
Intelligent Alternator Control (IAC), as discussed earlier, optimizes the engine fuel consumption, by optimizing the electrical energy generation and storage. There are three major functions of IAC – 1.
Battery SOC Control / Alternator Shutdown – When the battery is charged adequately, alternator is shut down, that is the output voltage of the alternator is reduced well below the battery voltage to ensure that there is no current output. This function is aimed at maintaining the battery SOC at a level which ensures the startability across the operating temperatures, and more importantly, a level at which the battery accepts higher charging current.
2.
Energy Recuperation (ER) – ER is similar to Regenerative Braking in Electric Vehicles. When the vehicle is decelerating, the alternator is operated at a slightly higher output voltage to
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recuperate or recover a part of the vehicle’s kinetic energy and store it into the battery. Output voltage of the Alternator during the ER, are in the range of 15 V to 16 V. Battery charge acceptance is higher at slightly elevated voltages and it ensures maximum possible energy recuperation.
3.
Passive Torque Boost – When the driver demands quick acceleration, alternator is shut down to reduce the torque demand on the engine, to improve the drivability.
Realization of these two function is explained in the following sections.
2.5.1 Control System Architecture Figure 22 shows the architecture of the control system for a MHS, with the boundary of the logical system (internal to Micro Hybrid Controller) highlighted.
Figure 22. Architecture of the Micro Hybrid Control System. BMS receives the battery related information from IBS on Local Interconnect Network (LIN), which is a preferred serial data protocol for low speed and low data transfer requirements. In addition, BMS receives other signals like crank enable signal, etc., on hardwired interface. BMS generates necessary control signals which are routed to AMS, WLM, and ESS. AMS performs the functions of Intelligent Alternator Control, as discussed in [1] and in the previous sections of this paper. WLM is an intermediate module between MHS and the HMI Device through which the faults or related information is provided to the driver. ESS performs the control of Engine Stop and Restart. 2.5.1.1 Battery Management System Although most of the functions of a Battery Management System (BMS), like estimation of State of Charge, State of Health, and State of Function are performed by IBS, a MHS must have a BMS to augment the IBS. Usual functions of a BMS in a MHS are – 1.
Implementing Diagnostic Services on Signals Received by IBS.
2.
Filtering and processing of the raw signals from IBS like Battery Voltage and Current. (In some cases, resolution of the battery current signal from the IBS is different in different ranges. Thus, the BMS must process such signals to make them readable and usable).
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3.
Generating necessary internal signals for control of other modules of MHS.
4.
Some functions, like temperature compensation for battery charging, which are inbuilt to alternator regulator in a conventional vehicle.
5.
Signal routing and management.
6.
Implement services for End of Line and Diagnostic Checks.
More details about the IAC and BMS are discussed in [2.1], [2.2], and [2.3]. Table 3 lists some of the important outputs from a BMS. Table 3 – Typical Outputs from BMS Sl. #
Signal Name
Range
Description
Destination Module
1
Battery SOC
0 – 100%
2
Battery SOH
0 – 100%
3
4
5
6
7
8
9
Battery SOF – Voltage Peak
Battery SOF – Voltage Peak Wrong Battery Flag End of Charge Flag End of Discharge Flag Weak Cell Flag Acid Stratification Flag
State of Charge of Battery received form IBS State of Health of Battery received from IBS
AMS, ESS, WLM
AMS, ESS, WLM
State of Function – Estimated 0 to 16 V
Voltage dip of the battery for the
AMS, ESS
next crank event State of Function – Estimated 0 to 16 V
remaining energy reserve in the
AMS, ESS
battery for the next crank event 0-1
Indication if a wrong battery is
(True/False) 0-1
installed on the vehicle Indication of battery being close to
(True/False) 0-1
100% SOC Indication of battery being close to
(True/False) 0-1
0% SOC Indication of a Weak Cell within the
(True/False) 0-1 (True/False)
battery Indication of acid stratification
AMS, ESS, WLM
AMS, ESS, WLM
AMS, ESS, WLM
AMS, ESS, WLM
AMS, ESS, WLM
These flags indicate whether the
10
Measurement Plausibility Flags
direct measurements (Battery
0-1 (True/False)
Voltage, Current, and Temperature)
AMS, ESS, WLM
are plausible (correct) or implausible (possible error)
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2.5.1.2 Alternator Management System Alternator Management System (AMS) generates the control commands for the IAL. AMS is modelled as finite state-space model, involving the different states of the alternator control. As discussed earlier, there are three major functions of IAC, which constitute three distinct states of operation for the IAL. These states are discussed as follows – 1.
Alternator Shutdown – Alternator Shutdown means ensuring that IAL will not provide any current output to the loads. This is achieved by reducing the output voltage of the IAL to a level of 10.6 Volts, by reducing the excitation current to the rotor. As the output voltage of the IAL is lower than the battery voltage (typically in the range of 11.2 to 12.8 Volts based on the battery SOC), the output current from the alternator is zero, and the vehicle electrical system is supported by the battery.
2.
Normal State – IAL runs in the normal output voltage of 14 to 14.5 Volts in this state, and the excitation current is not limited so as to support all the loads and charging of the battery as per the demand.
3.
Recuperation – In this state, the IAL output will be increased to 15.5 to 16 Volts, so that the alternator output is increased and the battery is charged quickly, only when the vehicle is decelerating or is under braking.
The transition between these states is controlled by the algorithm is shown in Figure 23.
Figure 23 – State Control Machine for AMS
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State transitions occur as per the transitions conditions which are illustrated in Table 4. Table 4 – State Transition Control for AMS Transition T12 T21, T61, T31, T51 T23
Condition Engine RPM > 0 && Engine RPM 0) && Battery SOC >= 82%
Excitation Current = 0 A
(Vehicle Acceleration == 0 OR Vehicle Acceleration
Output Voltage = 14.5 V
> 0) && Battery SOC
