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Fault Diagnosis of Power Batteries Based on Local Mean Decomposition and Local Outlier Factor
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Jie HU1, 2, 3, Chaoming JIA1, 2, 3, Yayu CHENG1, 2, 3, Hai YU1, 2, 3
Chinese Journal of Automotive Engineering | 2024, 14(3) : 422 - 432
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Chinese Journal of Automotive Engineering | 2024, 14(3): 422-432
• Intelligent Safety/Security Technologies and Test/Evaluation •
Fault Diagnosis of Power Batteries Based on Local Mean Decomposition and Local Outlier Factor
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Jie HU1, 2, 3, Chaoming JIA1, 2, 3, Yayu CHENG1, 2, 3, Hai YU1, 2, 3
Affiliations
  • 1 Hubei Key Laboratory of Modern Auto Parts Technology Wuhan University of Technology Wuhan 430070 China
  • 2 Auto Parts Technology Hubei Collaborative Innovation Center Wuhan University of Technology Wuhan 430070 China
  • 3 Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering Wuhan 430070 China
doi: 10.3969/j.issn.2095-1469.2024.03.10
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The diagnosis of power battery faults is crucial for the normal operation of electric vehicles. In response, this paper proposes a power battery fault diagnosis method using local mean decomposition and the local outlier factor, aimed at fault recognition and localization within battery packs. Firstly, the voltage signal is preprocessed through local mean decomposition, followed by the reconstruction of the voltage signal according to the correlation coefficient. Furthermore, the kurtosis factor of the reconstructed signal is extracted as the fault feature input to the local outlier factor algorithm, which then identifies the faulty battery based on an adaptive threshold. Finally, the proposed method is validated on a real vehicle, effectively and accurately detecting faults while demonstrating the reliability and robustness of the method.

local mean decomposition  /  kurtosis  /  fault diagnosis  /  local outlier factor  /  power battery
Jie HU, Chaoming JIA, Yayu CHENG, Hai YU. Fault Diagnosis of Power Batteries Based on Local Mean Decomposition and Local Outlier Factor[J]. Chinese Journal of Automotive Engineering, 2024 , 14 (3) : 422 -432 . DOI: 10.3969/j.issn.2095-1469.2024.03.10
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Article Info
doi: 10.3969/j.issn.2095-1469.2024.03.10
  • Receive Date：2023-12-12
  • Online Date：2025-07-21
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History
  • Received：2023-12-12
  • Revised：2024-01-21
Funding
Affiliations
    1 Hubei Key Laboratory of Modern Auto Parts Technology Wuhan University of Technology Wuhan 430070 China
    2 Auto Parts Technology Hubei Collaborative Innovation Center Wuhan University of Technology Wuhan 430070 China
    3 Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering Wuhan 430070 China
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