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

机译:电动汽车锂离子电池组的一种新型故障诊断方法

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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.
机译:本文侧重于基于杂机相关系数(ICC)方法的故障检测,用于保证电动车辆的安全可靠性(EVS)。 所提出的方法通过捕获偏移电压降,从电动车辆的服务和管理中心提取电压来计算ICC值。 ICC值用于通过ICC原理分析电池故障。 ICC值不仅通过放大电压差而具有先进的故障分辨率,还可以通过设置移动窗口来延长故障内存。 此外,第一和最后一个电压的环形接头设计用于定位电池组中的故障。 此外,采用模拟和实验来验证和分析电压故障。 基于仿真验证,将适当大小的移动窗口设置为确保故障检测方法的灵敏度。 实验结果表明该方法可以适当地检测EVS的故障信号。

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