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A novel fault diagnosis method for lithium-Ion battery packs of electric vehicles

  • Beijing Institute of Technology

科研成果: 期刊稿件文章同行评审

摘要

This paper focuses on fault detection based on interclass correlation coefficient (ICC) method for guaranteeing safe and reliable of electric vehicles (EVs). The proposed method calculates ICC values by capturing the off-trend voltage drop and the voltages are extracted from Service and Management Center of electric vehicles. The ICC value is employed to analyze battery fault by ICC principle. The ICC value not only has advanced fault resolution by amplifying the voltage difference, but also can prolong the fault memory by setting moving windows. Moreover, a loop joints the first and last voltages is designed to locate faults in battery pack. In addition, simulation and experiment are employed to validate and analyze the voltage faults. Based on the simulation verification, the appropriate size of moving windows is set to ensuring sensitivity of fault detection method. The experiment results indicate the method can appropriately detect fault signals for EVs.

源语言英语
页(从-至)402-411
页数10
期刊Measurement: Journal of the International Measurement Confederation
116
DOI
出版状态已出版 - 2月 2018

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  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

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