Fault Diagnosis of Lithium-Ion Batteries Based on the Historical Trajectory of Remaining Discharge Capacity

被引:0
|
作者
Jiang, Jiuchun [1 ]
Qu, Bingrui [2 ]
Liu, Shuaibang [1 ]
Yan, Huan [2 ]
Zhang, Zhen [2 ]
Chang, Chun [2 ]
机构
[1] Beijing Inst Technol, Shenzhen Automot Res Inst, Shenzhen 518118, Peoples R China
[2] Hubei Univ Technol, Hubei Key Lab High Efficiency Utilizat Solar Energ, Wuhan 430000, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 23期
关键词
lithium-ion battery; fault diagnosis; medium and long time scale; historical trajectory;
D O I
10.3390/app142310895
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In recent years, the number of safety accidents in new-energy electric vehicles due to lithium-ion battery failures has been increasing, and the lithium-ion battery fault diagnosis technology is particularly important to ensure the safe operation of electric vehicles. This paper proposes a method for lithium-ion battery fault diagnosis based on the historical trajectory of lithium-ion battery remaining discharge capacity in medium and long time scales. The method first utilizes the sparrow search algorithm (SSA) to identify the parameters of the second-order equivalent circuit model of the lithium-ion battery, and then estimates the state of charge (SOC) of the lithium-ion battery using the extended Kalman filter (EKF). The remaining discharge capacity is estimated according to the SOC, and finally the feature vectors are used to diagnose the faults using box plots on the medium and long time scales. Experimental results verify that the root mean squared error (RSME) and mean absolute error (MAE) of the proposed SOC estimation method are 0.0049 and 0.0034, respectively. This method can accurately identify the faulty single cell in a battery pack with low-capacity single cells and promptly detect any abnormalities in the single cell when a micro-short circuit fault occurs.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Remaining useful life prognostics of lithium-ion batteries based on a coordinate reconfiguration of degradation trajectory and multiple linear regression
    Chen, Zhiwei
    Li, Lianfeng
    Cui, Weiwei
    Yang, Song
    Wang, Yao
    Wang, Dexin
    FRONTIERS IN ENERGY RESEARCH, 2023, 10
  • [42] Fault diagnosis of lithium-ion batteries based on wavelet packet decomposition and Manhattan average distance
    Liao, Li
    Yang, Da
    Li, Xunbo
    Jiang, Jiuchun
    Wu, Tiezhou
    INTERNATIONAL JOURNAL OF GREEN ENERGY, 2024, 21 (12) : 2828 - 2842
  • [43] Fault diagnosis method for lithium-ion batteries in electric vehicles based on isolated forest algorithm
    Jiang, Jiuchun
    Li, Taiyu
    Chang, Chun
    Yang, Chen
    Liao, Li
    JOURNAL OF ENERGY STORAGE, 2022, 50
  • [44] A Hybrid Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles
    Jiang, Jiuchun
    Cong, Xinwei
    Li, Shuowei
    Zhang, Caiping
    Zhang, Weige
    Jiang, Yan
    IEEE ACCESS, 2021, 9 : 19175 - 19186
  • [45] Recent advances in model-based fault diagnosis for lithium-ion batteries: A comprehensive review
    Xu, Yiming
    Ge, Xiaohua
    Guo, Ruohan
    Shen, Weixiang
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2025, 207
  • [46] A Comprehensive Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles
    Cong, Xinwei
    Zhang, Caiping
    Jiang, Jiuchun
    Zhang, Weige
    Jiang, Yan
    Zhang, Linjing
    ENERGIES, 2021, 14 (05)
  • [47] Remaining Useful Life Estimation of Lithium-Ion Batteries based on Thermal Dynamics
    Zhang, Dong
    Dey, Satadru
    Perez, Hector E.
    Moura, Scott J.
    2017 AMERICAN CONTROL CONFERENCE (ACC), 2017, : 4042 - 4047
  • [48] Model-based real-time thermal fault diagnosis of Lithium-ion batteries
    Dey, Satadru
    Biron, Zoleikha Abdollahi
    Tatipamula, Sagar
    Das, Nabarun
    Mohon, Sara
    Ayalew, Beshah
    Pisu, Pierluigi
    CONTROL ENGINEERING PRACTICE, 2016, 56 : 37 - 48
  • [49] Remaining Useful Life Prediction of Lithium-ion Batteries Based on a Hybrid Model
    Lv, Haizhen
    Shen, Dongxu
    Yang, Zhigang
    2022 IEEE 17TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2022, : 1003 - 1008
  • [50] Remaining life prediction of lithium-ion batteries based on health management: A review
    Song, Kai
    Hu, Die
    Tong, Yao
    Yue, Xiaoguang
    JOURNAL OF ENERGY STORAGE, 2023, 57