Towards a smarter battery management system: A critical review on battery state of health monitoring methods

被引:675
作者
Xiong, Rui [1 ]
Li, Linlin [1 ]
Tian, Jinpeng [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Dept Vehicle Engn, 5 South Zhongguancun St, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicles; Lithium-ion battery; State of health; Degradation; Capacity; Impedance; LITHIUM-ION BATTERIES; TIME POWER MANAGEMENT; ENERGY-STORAGE SYSTEM; SINGLE-PARTICLE MODEL; ON-BOARD STATE; CYCLE-LIFE; OF-CHARGE; CAPACITY ESTIMATION; ELECTRIC VEHICLES; POLYMER BATTERY;
D O I
10.1016/j.jpowsour.2018.10.019
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
To ensure the driving safety and avoid potential failures for electric vehicles, evaluating the health state of the battery properly is of significant importance. This study aims to serve as a useful support for researchers and practitioners by systematically reviewing the available literature on state of health estimation methods. These methods can be divided into two types: experimental and model-based estimation methods. Experimental methods are conducted in a laboratory environment to analyze battery aging process and provide theoretical support for model-based methods. Based on a battery model, model-based estimation methods identify the parameters, which have certain relationships with battery aging level, to realize state of health estimation. On the basis of reading extensive literature, methods for determining the health state of the battery are explained in a deeper way, while their corresponding strengths and weaknesses of these methods are analyzed in this paper. At the end of the paper, conclusions for these methods and prospects for the development trend of health state estimation are made.
引用
收藏
页码:18 / 29
页数:12
相关论文
共 50 条
[31]   A comprehensive review of the lithium-ion battery state of health prognosis methods combining aging mechanism analysis [J].
Xiao, Yanqiu ;
Wen, Jishu ;
Yao, Lei ;
Zheng, Jie ;
Fang, Zhanpeng ;
Shen, Yongpeng .
JOURNAL OF ENERGY STORAGE, 2023, 65
[32]   Solid-State Batteries: Chemistry, Battery, and Thermal Management System, Battery Assembly, and Applications-A Critical Review [J].
Bicer, Emre ;
Aksoz, Ahmet ;
Bakar, Recep ;
Odabasi, Cagla ;
Vonk, Willar ;
Soares, Maria Ines ;
Goncalves, Rafaela ;
Lourenco, Emanuel ;
Uzel, Atakan ;
Aksoy, Tulay ;
Haste, Zeynep Ozserce ;
Oral, Burcu ;
Eroglu, Omer ;
Asal, Burcak ;
Oyucu, Saadin .
BATTERIES-BASEL, 2025, 11 (06)
[33]   An online state of health estimation method based on battery management system monitoring data [J].
Liu, Fang ;
Liu, Xinyi ;
Su, Weixing ;
Lin, Hui ;
Chen, Hanning ;
He, Maowei .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2020, 44 (08) :6338-6349
[34]   Blockchain review for battery supply chain monitoring and battery trading [J].
Rufino Junior, Carlos Antonio ;
Sanseverino, Eleonora Riva ;
Gallo, Pierluigi ;
Koch, Daniel ;
Schweiger, Hans-Georg ;
Zanin, Hudson .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2022, 157
[35]   A Review of Lithium-Ion Battery State of Health Estimation and Prediction Methods [J].
Yao, Lei ;
Xu, Shiming ;
Tang, Aihua ;
Zhou, Fang ;
Hou, Junjian ;
Xiao, Yanqiu ;
Fu, Zhijun .
WORLD ELECTRIC VEHICLE JOURNAL, 2021, 12 (03)
[36]   Battery prognostics and health management from a machine learning perspective [J].
Zhao, Jingyuan ;
Feng, Xuning ;
Pang, Quanquan ;
Wang, Junbin ;
Lian, Yubo ;
Ouyang, Minggao ;
Burke, Andrew F. .
JOURNAL OF POWER SOURCES, 2023, 581
[37]   Battery state estimation methods and management system under vehicle-cloud collaboration: A Survey [J].
Mei, Peng ;
Karimi, Hamid Reza ;
Xie, Jiale ;
Chen, Fei ;
Ou, Lei ;
Yang, Shichun ;
Huang, Cong .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2024, 206
[38]   An Overview of Methods and Technologies for Estimating Battery State of Charge in Electric Vehicles [J].
Marques, Taysa Millena Banik ;
dos Santos, Joao Lucas Ferreira ;
Castanho, Diego Solak ;
Ferreira, Mariane Bigarelli ;
Stevan Jr, Sergio L. L. ;
Font, Carlos Henrique Illa ;
Alves, Thiago Antonini ;
Piekarski, Cassiano Moro ;
Siqueira, Hugo Valadares ;
Correa, Fernanda Cristina .
ENERGIES, 2023, 16 (13)
[39]   Exploiting domain knowledge to reduce data requirements for battery health monitoring [J].
Tian, Jinpeng ;
Ma, Liang ;
Zhang, Tieling ;
Han, Te ;
Mai, Weijie ;
Chung, C. Y. .
ENERGY STORAGE MATERIALS, 2024, 67
[40]   Enhanced battery health monitoring in electric vehicles: A novel hybrid HBA-HGBR model [J].
Liao, Wenjun ;
Chen, Zilong ;
Li, Pingfei ;
Tan, Jinhui ;
Li, He ;
Zhao, Chengyi .
JOURNAL OF ENERGY STORAGE, 2025, 110