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

被引:138
|
作者
Li, Xiaoyu
Wang, Zhenpo [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicles; Fault diagnosis; Lithium-ion batteries; Interclass correlation coefficient; Service and management center for electric; THERMAL RUNAWAY; MODEL; STATE; ENERGY; SIMULATION; MANAGEMENT; SYSTEM; SOC; PREDICTION; DISCHARGE;
D O I
10.1016/j.measurement.2017.11.034
中图分类号
T [工业技术];
学科分类号
08 ;
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.
引用
收藏
页码:402 / 411
页数:10
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