Battery management systems (BMS) optimization for electric vehicles (EVs) in Malaysia P. M. W. Salehen, M. S. Su’ait, H. Razali, and K. Sopian
Citation: AIP Conference Proceedings 1831, 020032 (2017); doi: 10.1063/1.4981173 View online: http://dx.doi.org/10.1063/1.4981173 View Table of Contents: http://aip.scitation.org/toc/apc/1831/1 Published by the American Institute of Physics
Articles you may be interested in Energy consumption in residential building: The effect of appliances and human behaviour AIP Conference Proceedings 1831, 020018020018 (2017); 10.1063/1.4981159 Flow characteristics of 3-D turning diffuser using particle image velocimetry AIP Conference Proceedings 1831, 020021020021 (2017); 10.1063/1.4981162 The system design and performance test of hybrid vertical axis wind turbine AIP Conference Proceedings 1831, 020030020030 (2017); 10.1063/1.4981171 One dimensional modeling of a diesel-CNG dual fuel engine AIP Conference Proceedings 1831, 020036020036 (2017); 10.1063/1.4981177 Studies on modification of ZnO sol-gel spin coated on flexible substrate at low temperature: Effect of time exposure AIP Conference Proceedings 1831, 020033020033 (2017); 10.1063/1.4981174
Battery Management Systems (BMS) Optimization for Electric Vehicles (EVs) in Malaysia P. M.W. Salehen1, M.S. Su’ait 2, H. Razali3,a) and K. Sopian4 1
Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia 2,3,4 Department of Mechanical Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia a)
[email protected]
Abstract. Following the UN Climate Change Conference 2009 in Copenhagen, Denmark, Malaysia seriously committed on “Go Green” campaign with the aim to reduce 40% GHG emission by the year 2020. Therefore, the National Green Technology Policy has been legalised in 2009 with transportation as one of its focused sectors, which include hybrid (HEVs), electric vehicles (EVs) and fuel cell vehicles with the purpose of to keep up with the worst scenario. While the number of registered cars has been increasing by 1 million yearly, the amount has doubled in the last two decades. Consequently, CO2 emission in Malaysia reaches up to 97.1% and will continue to increase mainly due to the activities in the transportation sector. Nevertheless, Malaysia is now moving towards on green car which battery-based EVs. This type of transportation mainly needs power performance optimization, which is controlled by the Batteries Management System (BMS). BMS is an essential module which leads to reliable power management, optimal power performance and safe vehicle that lead back for power optimization in EVs. Thus, this paper proposes power performance optimization for various setups of lithium-ion cathode with graphene anode using MATLAB/SIMULINK software for better management performance and extended EVs driving range.
INTRODUCTION Batteries are widely used as the main energy source in many applications, from portable electronics to electric vehicles (EVs). The revolution in battery technology has created interests in the development of batteries for EVs since the mid-19th century when the first EV came into existence. Now, EVs can reduce up to 75% oil consumption. Hence, EV batteries have gained attention in the global vehicle market. The Boston Consulting Group also reported that advanced batteries for electric vehicles is expected to reach US $25 billion by 2020 in the global market, and this is three times the size of today’s entire lithium-ion battery market for consumer electronics. The U.S. Advanced Battery Consortium (USABC)) and the U.S. Council for Automotive Research (USCAR) have set minimum goals for battery characteristics for long-term commercialization of advanced batteries in EVs and hybrid electric vehicles (HEVs). In order to enlarge the market share of EVs and HEVs, safety and reliability are the top concerns by users. However, safety and reliability are subjected not only to battery technologies, but also the management system of the battery. Therefore, a battery management system (BMS) plays a vital role in improving battery performance and optimizing vehicle operation in a safe and reliable manner because BMS is the connector between the battery and the vehicle. Consequently, considering the rapid growth of EV and HEV markets, there is an urgent need to develop a comprehensive and mature BMS.
7th International Conference on Mechanical and Manufacturing Engineering AIP Conf. Proc. 1831, 020032-1–020032-6; doi: 10.1063/1.4981173 Published by AIP Publishing. 978-0-7354-1499-0/$30.00
020032-1
Current BMSs in Malaysia The Malaysian Green Technology Corporation (MGTC) and the Malaysia Automotive Institute (MAI) are established as the green authority agencies who spearhead the aims to fast-track the implementation of the Electric Vehicles (EV) policy and regulations for public and private transportations, upon the commitment of the Malaysian government during the UN Climate Change Summit, Copenhagen (COPs 15) in Denmark. The said commitment is to reduce the 2005 greenhouse gases level by 40% by the year 2020. Subsequently, Malaysia targets for 100,000 electric cars and 2,000 electric buses on the road by 2020. The Prime Minister of Malaysia launched the National Automotive Policy (NAP) and the National Green Technology Policy on 24th July 2009 to emphasize the development and promotion of green vehicles. To date, 97.1% of CO2 emission in Malaysia is caused by the conventional internal combustion engines (ICEs) energy activities. Consequently, one of the focus factors in the National Green Technology policy is transportation, which is the second highest contributor of carbon emission, while the NAP promotes hybrid and electric vehicles and the development of the related infrastructure [1][2]. In addition, a study entitled Assessment of Greenhouse Gas Emission Reduction Measures in Transportation Sector of Malaysia found that a vast portion of national GHG emissions in Malaysia originate from the transportation sector [3]. Since the EV industry in Malaysia has just started, this study is very significant as it will provide insights on the knowledge contribution and innovation invention for EV industries towards the year 2020. Furthermore, this study is the first of its kind in Malaysia. Therefore, it can benefit in term of training public and private institutions on the optimization of BMS for EVs in Malaysia. The knowledge on BMS as an electronic device component, which connects between the charger and the battery of a hybrid or electric vehicle (EV) system should be explored. The function of BMS is not limited to charge-discharge operation. Rather, it can be considered as the brain behind battery packs or a vital component for a battery-based electrical vehicle. BMS is mainly used for two critical functions which are system protection, which is the single most important function, and energy management. The current commercial BMS is able to provide critical safeguards to protect the battery from damage. This is because BMS can manage the output, command the charge-discharge input and provide notification on the status of the battery packs. For energy management, BMS is used for estimating driving range, monitoring the state of the battery and evaluating the State of Charge (SOC) as well as State of Health (SOH) [1]. This concept of energy management is similar to that in conventional gasoline car or internal combustion engine (ICE), which manages the engine system through the status shown by the fuel gauge meter. Nevertheless, the EVs industry in Malaysia is still growing and it is great to see that Malaysia is taking measures to ensure that the future of electric cars will be a promising one. Since the impact of electric cars is more than being energy efficient and having cleaner emissions than a HEV, it is better in term of conserving the environment compared to conventional ICEs. Hence, EVs is the best option for being environmentallyfriendly in the future. Its safety and reliability are not only subjected to the technology of the battery, but also the BMS module, which will lead to reliable power management, optimal power performance and safe vehicles, that lead back for power optimization in EVs.
BATTERY ENERGY TECHNOLOGY AND BATTERY MANAGEMENT SYSTEM BMS means differently for different people. Some people may define BMS as a simple battery monitor that is able to track key functional parameters during the charging and discharging of the voltages, currents, and also temperature of the internal battery and ambient temperatures. The BMS monitoring circuit is responsible to deliver inputs to protect the devices by disconnecting the battery from the load or charger if any of the parameter reaches beyond its limit, which is shown on the BMS indicator through alarm signal notification. Hence, BMS is not only important for battery monitoring and protection, but it also prolongs its life and keeps it ready for full power delivery when required. All of these are inclusive of monitoring the charging regime up to the intentional maintenance. To date, BMS application is widely used in small electronic devices up to automotive machinery such as electric vehicles (EVs) and hybrid electric vehicles (HEVs). In comparison, the number of cells in a vehicle’s battery is thousands times greater than that in portable electronic devices. As a consequence, lithium ion battery (LIB) is the most promising battery energy technology for EVs due to their trustworthy properties such as high energy density, long life cycle and low self-discharge. Thus, due to these reasons, lithium ion battery is significantly and widely developed for generating EVs and HEVs since the 1990s. Figure 1 shows the commercial evolution of rechargeable to higher density batteries and
020032-2
so forth. Furthermore, the batteries for vehicles are also designed to be of high-powered system performance instead of only for lifelong energy storage system. This requires the BMS for EVs to be more complex than those used for portable electronic devices as the batteries for HEVs and EVs need to deliver high voltage and high current. Nevertheless, a similar functions is provided by the BMS in each case [4]. Therefore, avoiding hazardous situations necessitates the adoption of a proper BMS design so that each cell in the battery is maintained within the safe and reliable operating range. Applications with a large number of cells may require voltage of up to 400 V [5]. These basic concepts can be illustrated in the generic BMS architecture design with basic functions as shown in Figure 2. LIB chemistry is also well acknowledged as the technology of choice for energy storage in EVs for sustainable mobility. Nevertheless, further development in the area needs further research, which include the best choice for cell material and the development of electronic circuits and algorithms for a more effective battery utilization for EVs [5]. Battery parameters to be considered for BMS optimization are voltage, current, and temperature, which can be applied to forecast the SOC of the battery [9]. Another challenge for vehicle performance related to BMS is the thermal management system, which is required to preserve the optimal cell performance and also to achieve a full battery lifespan [10]. A research reported that a fast charging of ten-minute period can move a vehicle up to 100 miles and provide enough energy in EV battery packs [6]. Thus, with the aim to lengthen battery lifespan, BMS in EV plays a vital role as it controls the operation of the battery [7]. Furthermore, it is very important for BMS to maintain the battery’s reliability and safety, ensure proper state monitoring and evaluation, ensure functional cell balancing and charge control. Additionally, the battery chemistry is an electrochemical device, it will also act differently under different operational and environmental conditions. Due to the uncertainty of the battery’s performance, it is challenging to implement these functions [4]
FIGURE 1. Commercial evolution of rechargeable batteries to higher density
020032-3
FIGURE 2. An illustration of BMS architecture showing the Cell Monitoring Unit (CMU), the Module Management Unit (MMU) and the Pack Management Unit (PMU). MSU is the Main Switch Unit. Source: Brandl et al. (2012)
PROJECTED BMS OPTIMIZATION
Figure 3. EV Schematic Diagram
020032-4
The need for more power will lead to a large voltage supply that is very difficult to be acquired from battery power. Literature review reveals the development of battery technology using ultra-capacitors (UCs) in automotive as a solution to this problem [11]. Although UCs have high power density, it is still lower compared to batteries. Therefore, the development of the combination of battery and ultra-capacitor as hybrid energy or so-called as Hybrid Energy Storage Systems (HESS) as shown in Figure 5 is imperative. The combination proposes a better performance compared to using either individually. Figure 5 below outlines the proposed HESS.
Figure 4. Illustration of HESS configuration. Source: [11]
Therefore, this study emphasizes on using MATLAB/SIMULINK software for the optimization of power generation using various compounds lithium-ion cathode with graphene anode in order to attain the experimental performance data (charge-discharge, power capacity and life cycles). Hence, based on literature review, this paper can propose a new method for BMS optimization for greater management performance and extended driving range of electric car in order to satisfy the development of BMS prognostic model. Finally, better performance of BMS and optimized power performance of EV will lead to increased reliability. This study is also vital in Malaysia especially as it is the first literature on the development of the BMS in addition to electric vehicle batteries in Malaysia.
CONCLUSIONS It is very important for BMS to be well-maintained for battery reliability and safety, proper state monitoring and evaluation, and functional cell balancing and charge control. Due to these reasons, there is a need for BMS optimization for EVs to increase the reliability of BMS and optimize EVs power performance. Hence, further from the literature reviewed analysis, this paper can offer a new method for BMS optimization for better management performance and extended electric car driving range to satisfy the development of BMS prognostic model. It is expected to provide future innovation in the EV industries towards the year 2020 or beyond. Moreover, the target of reducing greenhouse gas (GHG) emission by up to 40% towards the year 2020 will be achievable.
ACKNOWLEDGEMENT The authors would like to extend their gratitude towards Universiti Kebangsaan Malaysia (UKM) for allowing this research to be carried out. This work is supported by the Research University Grant, TD-2015-08.
020032-5
REFERENCES 1. 2. 3. 4. 5.
6. 7. 8. 9. 10. 11.
Malaysia Automotive Institute (MAI), “National Automotive Policy (NAP) 2014,” 2014. [Online]. Available: http//www.mai.org.my. Malaysia Automotive Institute (MAI), “Transportation is one of the main emphasized sector as it is the 2nd. Highest contributor in term of carbon emission.,” 2014. [Online]. Available: http//www.mai.org.my. S. Shamsudin, & Minhans, A., and O. C. Puan, “Assessment of Greenhouse Gas Emission Reduction Measures in Transportation Sector of Malaysia,” J. Teknol., vol. 4, no. 70, pp. 1–8, 2014. Y. Xing, E. W. M. Ma, K. L. Tsui, and M. Pecht, “Battery management systems in electric and hybrid vehicles,” Energies, vol. 4, no. 11. pp. 1840–1857, 2011. M. Brandl, H. Gall, M. Wenger, V. Lorentz, M. Giegerich, F. Baronti, G. Fantechi, L. Fanucci, R. Roncella, R. Saletti, S. Saponara, A. Thaler, M. Cifrain, and W. Prochazka, “Batteries and battery management systems for electric vehicles,” Des. Autom. Test Eur. Conf. Exhib. (DATE), 2012, no. September 2015, pp. 971–976, 2012. C. Botsford and A. Szczepanek, “Fast Charging vs . Slow Charging : Pros and cons for the New Age of Electric Vehicles,” in EVS24, 2009, no. May, pp. 1–9. R. Adany, D. Aurbach, and S. Kraus, “Switching algorithms for extending battery life in Electric Vehicles,” J. Power Sources, vol. 231, pp. 50–59, 2013. J. F. Rohan, M. Hasan, S. Patil, D. P. Casey, and T. Clancy, Energy Storage : Battery Materials and Architectures at the Nanoscale. 2014. Y. Wang and Y. Liu, “Electronic control system design and test of pure electric vehicle battery management system,” Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on. pp. 1289–1292, 2011. S. Chacko and Y. M. Chung, “Thermal modelling of Li-ion polymer battery for electric vehicle drive cycles,” J. Power Sources, vol. 213, pp. 296–303, 2012. M. Gopikrishnan, “Battery/ultra capacitor hybrid energy storage system for electric, hybrid and plug-in hybrid electric vehicles,” Middle - East J. Sci. Res., vol. 20, no. 9, pp. 1122–1126, 2014.
020032-6
