基于VMD的电动汽车电池组多故障在线诊断策略OA

Lithium-ion batteries have become an ideal power source for electric vehicles due to their high energy density,long cycle life,and no memory effect.However,the complex operating conditions of vehicles and the sus-ceptibility of battery packs to failure have a negative impact on the safe operation of electric vehicles.In view of the problem of fault diversity of existing battery packs,a multi-fault diagnosis method for battery packs based on the VMD(Variational Mode Decomposition)algorithm is proposed.The characteristics of battery voltage signal changes in bat-tery packs under different types of faults are analyzed,and the cross-voltage measurement circuits are used to con-struct unique fault features for different types of faults.Due to the fact that the fault features are not obvious,the VMD algorithm is adopted to extract the low-frequency components of the voltage signal,and the feature extraction method based on Manhattan distance is used to extract the fault features,and an online diagnosis scheme is designed.The experimental results show that the proposed method can quickly and accurately identify four types of faults in bat-tery packs and has certain noise robustness.