Diagnosis for Battery Module Inconsistencies Based on Electrochemical Impedance Spectroscopy

被引：0

作者：

Yao, Hanxin ^{[1
,2
]}

Wang, Xueyuan ^{[1
,2
]}

Yuan, Yongjun ^{[1
,2
,3
]}

Dai, Haifeng ^{[1
,2
]}

Wei, Xuezhe ^{[1
,2
]}

机构：

[1] School of Automotive Studies, Tongji University, Shanghai

[2] Clean Energy Automotive Engineering Center, Tongji University, Shanghai

[3] Shanghai Fire Cloud New Energy Technology Co. ，Ltd., Shanghai

来源：

Qiche Gongcheng/Automotive Engineering | 2024年 / 46卷 / 07期

关键词：

distribution of relaxation time; electrochemical impedance spectroscopy; inconsistency; lithium-ion batteries; unsupervised clustering;

D O I：

10.19562/j.chinasae.qcgc.2024.07.004

中图分类号：

学科分类号：

摘要：

There may be inconsistencies in temperature，charge state，aging state（capacity and internal resistance）between individual cells in a battery module. Due to the existence of the short board effect"，the inconsistencies will affect the overall performance of the battery module，so timely and accurate inconsistencies diagnosis is very necessary. Considering that the above-mentioned inconsistencies will affect the electrode process characteristics，which will be reflected in the Electrochemical Impedance Spectroscopy（EIS）and Distribution of Relaxation Time（DRT），in this paper，after clarifying the effect of several kinds of inconsistencies on EIS and DRT by combining the equivalent circuits，an inconsistencies diagnosis method for battery modules based on EIS and DRT is in-novatively proposed. The performance of unsupervised clustering algorithms such as K-means，AP（Affinity Propagation）and DBSCAN（Density Based Spatial Clustering of Applications with Noise）is comparatively analyzed by mixing the abnormal batteries into a group of batteries with good consistency. The results show that the DBSCAN diagnostic accuracy is 99.2%，which can realize the accurate diagnosis of the inconsistency difference of single cells within the battery module. © 2024 SAE-China. All rights reserved."

引用

页码：1167 / 1176

页数：9

共 20 条

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