Review of Management System and State-of-Charge Estimation Methods for Electric Vehicles

被引:5
|
作者
Sarda, Jigar [1 ]
Patel, Hirva [2 ]
Popat, Yashvi [3 ]
Hui, Kueh Lee [4 ]
Sain, Mangal [5 ]
机构
[1] Charotar Univ Sci & Technol, Chandubhai S Patel Inst Technol, M&V Patel Dept Elect Engn, Changa 388421, India
[2] Pandit Deendayal Energy Univ, Sch Technol, Dept Informat & Commun Technol, Gandhinagar 382007, India
[3] Charotar Univ Sci & Technol, Devang Patel Inst Adv Technol & Res, Comp Engn, Changa 388421, India
[4] Dong A Univ, Dept Elect Engn, Busan 49236, South Korea
[5] Div Comp & Informat Engn, Busan 49236, South Korea
来源
WORLD ELECTRIC VEHICLE JOURNAL | 2023年 / 14卷 / 12期
关键词
battery management system; SOC estimation; Kalman filter method; deep learning method; LITHIUM-ION BATTERIES; SOC ESTIMATION; LIFEPO4; BATTERIES; ONLINE ESTIMATION; ACCURATE STATE; MODEL; NETWORK; HYBRID; HEALTH; OBSERVER;
D O I
10.3390/wevj14120325
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Energy storage systems (ESSs) are critically important for the future of electric vehicles. Due to the shifting global environment for electrical distribution and consumption, energy storage systems (ESS) are amongst the electrical power system solutions with the fastest growing market share. Any ESS must have the capacity to regulate the modules from the system in the case of abnormal situations as well as the ability to monitor, control, and maximize the performance of one or more battery modules. Such a system is known as a battery management system (BMS). One parameter that is included in the BMS is the state-of-charge (SOC) of the battery. The BMS is used to enhance battery performance while including the necessary safety measures in the system. SOC estimation is a key BMS feature, and precise modelling and state estimation will improve stable operation. This review discusses the current methods used in BEV LIB SOC modelling and estimation. It also efficiently monitors all of the electrical characteristics of a battery-pack system, including the voltage, current, and temperature. The main function of a BMS is to safeguard a battery system for machine electrification and electric propulsion. The major responsibility of the BMS is to guarantee the trustworthiness and safety of the battery cells coupled to create high currents at high voltage levels. This article examines the advancements and difficulties in (i) cutting-edge battery technology and (ii) cutting-edge BMS for electric vehicles (EVs). This article's main goal is to outline the key characteristics, benefits and drawbacks, and recent technological developments in SOC estimation methods for a battery. The study follows the pertinent industry standards and addresses the functional safety component that concerns BMS. This information and knowledge will be valuable for vehicle manufacturers in the future development of new SOC methods or an improvement in existing ones.
引用
收藏
页数:33
相关论文
共 50 条
  • [21] A HARDWARE-ORIENTED DESIGN APPROACH FOR LIGHT ELECTRIC VEHICLES Onboard State-of-Charge Estimation
    Messier, Pascal
    Trovao, Joao Pedro F.
    LeBel, Felix-Antoine
    Pelletier, Louis
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2024, 19 (03): : 102 - 111
  • [22] Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles
    Li, Xiaoyu
    Wang, Zhenpo
    Zhang, Lei
    ENERGY, 2019, 174 : 33 - 44
  • [23] A Novel State-of-Charge Estimation Method for Lithium-Ion Battery Pack of Electric Vehicles
    Chen, Zheng
    Xia, Bing
    Mi, Chunting Chris
    2015 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC), 2015,
  • [24] Online estimation of model parameters and state-of-charge of LiFePO4 batteries in electric vehicles
    He, Hongwen
    Xiong, Rui
    Guo, Hongqiang
    APPLIED ENERGY, 2012, 89 (01) : 413 - 420
  • [25] Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles
    Espedal, Ingvild B.
    Jinasena, Asanthi
    Burheim, Odne S.
    Lamb, Jacob J.
    ENERGIES, 2021, 14 (11)
  • [26] State-of-charge estimation of the lithium-ion battery system with time-varying parameter for hybrid electric vehicles
    Zhang, Yun
    Zhang, Chenghui
    Zhang, Xianfu
    IET CONTROL THEORY AND APPLICATIONS, 2014, 8 (03): : 160 - 167
  • [27] Battery management system with state of charge indicator for electric vehicles
    Sun, Fengchun
    Zhang, Chengning
    Guo, Haitao
    Journal of Beijing Institute of Technology (English Edition), 1998, 7 (02): : 166 - 171
  • [28] A Review on the Battery State of Charge Estimation Methods for Electric Vehicle Battery Management Systems
    Aslan, Eyyup
    Yasa, Yusuf
    2019 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO 2019), 2019, : 281 - 285
  • [29] Overview of Lithium-Ion Battery Modeling Methods for State-of-Charge Estimation in Electrical Vehicles
    Meng, Jinhao
    Luo, Guangzhao
    Ricco, Mattia
    Swierczynski, Maciej
    Stroe, Daniel-Ioan
    Teodorescu, Remus
    APPLIED SCIENCES-BASEL, 2018, 8 (05):
  • [30] Recent developments and challenges in state-of-charge estimation techniques for electric vehicle batteries: A review
    Barik, Sucharita
    Saravanan, B.
    JOURNAL OF ENERGY STORAGE, 2024, 100