Micro-short circuit fault diagnosis of the parallel battery module based on increment capacity curve

被引:1
|
作者
Zhao, Xiuliang [1 ]
Wang, Jinzhi [1 ]
Zhao, Mingming [1 ]
Pan, Bangxiong [2 ]
Wang, Ruochen [1 ]
Wang, Limei [2 ]
Yan, Xueqing [3 ]
机构
[1] Jiangsu Univ, Sch Automot & Traff Engn, Zhenjiang 212013, Peoples R China
[2] Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Peoples R China
[3] Jiangsu Oliter Energy Technol Co Ltd, Yangzhou 225600, Peoples R China
基金
中国国家自然科学基金;
关键词
Parallel battery modules; Micro -short circuit fault; Incremental capacity curve; Fault diagnosis; MODEL; RESISTANCE;
D O I
10.1016/j.est.2024.111201
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Compared to individual cells and series packs, parallel battery modules (PBM) bring more difficult challenges to fault diagnosis due to the particularity of their structure and the self-balancing of each cell. In this paper, the PBM's micro-short circuit (MSC) fault diagnosis tests are firstly designed. Experimental results show that the smaller the short circuit resistance is, the greater the voltage curve deviates between the short circuit and the standard conditions. Moreover, the fault voltage curve of the parallel module shows less deviation from the standard voltage curve compared to the cells under the same conditions. Then, a fault simulation model for the PBM is built which is taken the resistance of the connector into consideration. Subsequently, the terminal voltage curve and incremental capacity (IC) curve characteristics of the PBM at different micro-shorted fault are analyzed. The results show that the difference of the fault characteristic peaks of the charge IC curve at a low Crate is more noticeable. Next, effective feature peaks for fault diagnosis are obtained by discussing the feasibility of different peaks. Further, the MSC fault of the parallel module is quantitatively diagnosed by analyzing the relationship between the amplitude of Peak III and Peak IV on the IC curve and short circuit resistance. It is found that the results of Peak IV diagnosis are more stable. Finally, a model-driven online calculated process of short circuit resistance in application is proposed and it has been verified for accuracy and robustness, with maximum diagnostic error of 6.06 %.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Micro Short Circuit Diagnosis Method of Battery Pack Based on Capacity Increment Curve and Charge Capacity Difference
    Zhang J.
    Gao X.
    Zhang L.
    Qiche Gongcheng/Automotive Engineering, 2023, 45 (02): : 191 - 198and230
  • [2] Micro-short circuit fault diagnosis of lithium-ion battery based on voltage curve similarity ranking volatility
    Chang, Chun
    Haimei, Cen
    Su, Guangwei
    Jiang, Jiuchun
    Tian, Aina
    Yan, Jiang
    Gao, Yang
    Wu, Tiezhou
    INTERNATIONAL JOURNAL OF GREEN ENERGY, 2024, 21 (11) : 2415 - 2428
  • [3] Electric vehicle battery pack micro-short circuit fault diagnosis based on charging voltage ranking evolution
    Chang, Chun
    Zhou, XiaPing
    Jiang, Jiuchun
    Gao, Yang
    Jiang, Yan
    Wu, Tiezhou
    JOURNAL OF POWER SOURCES, 2022, 542
  • [4] Early micro-short circuit fault diagnosis of lithium battery pack based on Pearson correlation coefficient and KPCA
    Fang, Le
    Liu, Shilin
    Cheng, Fanyong
    COMPUTERS & ELECTRICAL ENGINEERING, 2024, 118
  • [5] Quantitative diagnosis of micro-short circuit for lithium-ion batteries considering aging based on incremental capacity curve
    Liao, Li
    Hu, Xuantong
    Chen, Heng
    Wang, Zile
    Wu, Tiezhou
    Jiang, Jiuchun
    JOURNAL OF ENERGY STORAGE, 2024, 79
  • [6] A battery internal short circuit fault diagnosis method based on incremental capacity curves
    Sun, Jinlei
    Chen, Siwen
    Xing, Shiyou
    Guo, Yilong
    Wang, Shuhang
    Wang, Ruoyu
    Wu, Yuhao
    Wu, Xiaogang
    JOURNAL OF POWER SOURCES, 2024, 602
  • [7] Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs
    Kong, Xiangdong
    Zheng, Yuejiu
    Ouyang, Minggao
    Lu, Languang
    Li, Jianqiu
    Zhang, Zhendong
    JOURNAL OF POWER SOURCES, 2018, 395 : 358 - 368
  • [8] Online quantitative diagnosis algorithm for the internal short circuit of a lithium-ion battery module based on the remaining charge capacity
    Lai X.
    Li B.
    Meng Z.
    Li X.-J.
    Jin W.-T.
    Wang X.-J.
    Ma Y.-H.
    Zheng Y.-J.
    Gongcheng Kexue Xuebao/Chinese Journal of Engineering, 2023, 45 (01): : 158 - 168
  • [9] EMD-KPCA based Short Circuit Fault Diagnosis Method for Battery Pack
    Qian, Yuchen
    Lin, Han
    Proceedings of the IEEE International Conference on Industrial Technology, 2023, 2023-April
  • [10] A fault diagnosis method of battery internal short circuit based on multi-feature recognition
    Chen, Siwen
    Sun, Jinlei
    Tang, Yong
    Zhang, Fangting
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2024, 46 (11) : 2186 - 2197