Fault Diagnosis of Power Batteries Based on Local Mean Decomposition and Local Outlier Factor
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 decompositionkurtosisfault diagnosislocal outlier factorpower battery
国家科技期刊平台
NSTL
万方数据
维普
