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Cited by 580

The DOI matches its Crossref record; 151 of the 151 references it cites were found in a registry or an index.

Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures

Hu, Xiaosong, Zhang, Kai, Liu, Kailong, Lin, Xianke, Dey, Satadru, Onori, Simona·2020·IEEE Industrial Electronics Magazine

Abstract

Lithium (Li)-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles (EVs) and smart grids. However, various faults in a Li-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and diagnosis of various faults in LIBSs, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.

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Crossref · 10.1109/mie.2020.2964814

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Metadata

Authors
Hu, X., Zhang, K., Liu, K., Lin, X., Dey, S., & Onori, S.
Venue
IEEE Industrial Electronics Magazine
Published
2020-09
Volume
14
Issue
3
Pages
65-91
ISSN
  • 1932-4529 (ISSN-L)
  • 1941-0115
OpenAlex
W3088523737
Cited by
580
References
151
FWCI
24.60
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures. https://app.cochat.ai/papers/10.1109/mie.2020.2964814
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Hu, X., Zhang, K., Liu, K., Lin, X., Dey, S., & Onori, S. (2020). Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures. IEEE Industrial Electronics Magazine. https://doi.org/10.1109/mie.2020.2964814

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.