An Early Micro Internal Short Circuit Fault Diagnosis Method Based on Accumulated Correlation Coefficient for Lithium-Ion Battery Pack

被引:0
作者
Wang, Juntao [1 ]
Yang, Zhengye [1 ]
Wang, Shihao [1 ]
Yang, Hui [1 ]
Du, Mingzhe [1 ]
Song, Jifeng [2 ]
机构
[1] North China Elect Power Univ, Sch New Energy, Beijing 102206, Peoples R China
[2] North China Elect Power Univ, Inst Energy Power Innovat, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
lithium-ion battery pack; internal short circuit; fault diagnosis; correlation coefficient; ELECTRIC VEHICLES; MECHANISM;
D O I
10.3390/en17236071
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
Early micro internal short circuit (ISC) fault diagnosis is crucial for the safe and reliable operation of lithium-ion batteries. In order to solve the problem that the early micro ISC fault is difficult to identify due to its weak fault characteristics, this paper proposes a fault diagnosis method based on the accumulated correlation coefficient. Specifically, the method uses the accumulated voltage value within the time window as the input feature, constructs an adjustment factor based on the distance difference of the accumulated voltage value to amplify the difference between the fault voltage correlation coefficient and the normal voltage correlation coefficient, and finally achieves the purpose of highlighting the faulty cell. The effectiveness and diagnostic capability of the proposed method are verified in experiments of short circuit faults of different severity. The results show that the proposed method can effectively identify and locate early micro ISC faults within 200 s, and improve the diagnostic capability up to 0.02 C short-circuit severity. In addition, a multi-level diagnostic warning mechanism can be established according to the decrease of the fault voltage correlation coefficient, so as to measure the severity of the fault and track the fault evolution process.
引用
收藏
页数:19
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共 44 条
  • [1] A multi-fault diagnostic method based on category-reinforced domain adaptation network for series-connected battery packs
    Cai, Linhui
    Wang, Han
    Dong, Zhekang
    He, Zhiwei
    Gao, Mingyu
    Song, Yining
    [J]. JOURNAL OF ENERGY STORAGE, 2023, 60
  • [2] 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
    [J]. JOURNAL OF POWER SOURCES, 2022, 542
  • [3] Chen Zeyu, 2019, Journal of Mechanical Engineering, V55, P93
  • [4] Detecting the internal short circuit in large-format lithium-ion battery using model-based fault-diagnosis algorithm
    Feng, Xuning
    Pan, Yue
    He, Xiangming
    Wang, Li
    Ouyang, Minggao
    [J]. JOURNAL OF ENERGY STORAGE, 2018, 18 : 26 - 39
  • [5] Thermal runaway mechanism of lithium ion battery for electric vehicles: A review
    Feng, Xuning
    Ouyang, Minggao
    Liu, Xiang
    Lu, Languang
    Xia, Yong
    He, Xiangming
    [J]. ENERGY STORAGE MATERIALS, 2018, 10 : 246 - 267
  • [6] Micro-Short-Circuit Diagnosis for Series-Connected Lithium-Ion Battery Packs Using Mean-Difference Model
    Gao, Wenkai
    Zheng, Yuejiu
    Ouyang, Minggao
    Li, Jianqiu
    Lai, Xin
    Hu, Xiaosong
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (03) : 2132 - 2142
  • [7] Disturbance-Immune and Aging-Robust Internal Short Circuit Diagnostic for Lithium-Ion Battery
    Hu, Jian
    He, Hongwen
    Wei, Zhongbao
    Li, Yang
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (02) : 1988 - 1999
  • [8] Online multi-fault detection and diagnosis for battery packs in electric vehicles
    Kang, Yongzhe
    Duan, Bin
    Zhou, Zhongkai
    Shang, Yunlong
    Zhang, Chenghui
    [J]. APPLIED ENERGY, 2020, 259
  • [9] A review of early warning methods of thermal runaway of lithium ion batteries
    Kong, Depeng
    Lv, Hongpeng
    Ping, Ping
    Wang, Gongquan
    [J]. JOURNAL OF ENERGY STORAGE, 2023, 64
  • [10] Mechanism, modeling, detection, and prevention of the internal short circuit in lithium-ion batteries: Recent advances and perspectives
    Lai, Xin
    Jin, Changyong
    Yi, Wei
    Han, Xuebing
    Feng, Xuning
    Zheng, Yuejiu
    Ouyang, Minggao
    [J]. ENERGY STORAGE MATERIALS, 2021, 35 : 470 - 499