Fuzzy-Kalman-Filter-Based Short-Circuit Fault Diagnosis Design for Lithium-Ion Battery

被引:20
作者
Zhang, Haodong [1 ,2 ]
Liu, Zhitao [1 ,2 ]
Su, Hongye [1 ,2 ]
机构
[1] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China
[2] Zhejiang Univ, Inst Cyber Syst & Control, Hangzhou 310027, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Fault diagnosis; fuzzy Kalman filter (FKF); health difference feedback model (HDFM); lithium-ion batteries (LIBs); mean-difference model (MDM); short circuit (SC); INTERNAL SHORT-CIRCUIT; PACKS; MODEL; IDENTIFICATION; PARAMETER;
D O I
10.1109/TIE.2023.3270526
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, the health difference feedback model (HDFM) is proposed to diagnose the internal short-circuit fault of a lithium-ion battery. The HDFM combines the mean model with the median model. The algorithm uses the fuzzy Kalman filter with feedback to solve the problem of inaccurate estimation in the low-state-of-charge region and the influence of short-circuit current on the battery model. Through comparison and verification, the HDFM algorithm has all the advantages of the mean model and the median model and effectively avoids the disadvantages of both. Furthermore, it is shown in experiments that the HDFM algorithm can complete accurate diagnosis in a discharge cycle no matter what level of short-circuit fault it encounters.
引用
收藏
页码:2883 / 2892
页数:10
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