Voltage fault diagnosis of a power battery based on wavelet time-frequency diagram.

A fault diagnosis method for electric vehicle power batteries based on a time-frequency diagram is proposed. First, the original voltage signal is decomposed by improved variational mode decomposition to eliminate the influence of battery inconsistency on battery feature extraction. Then, the continuous wavelet transform is used to transform the one-dimensional signal into a two-dimensional time-frequency diagram, and the image entropy is used to reflect the characteristic parameters of the battery fault. Finally, the abnormal battery is marked with clustering algorithm. It is verified by real vehicle data that the proposed method can identify the battery fault and advance the identification time. • Decomposing voltage signals to reduce the impact of battery inconsistencies. • Extract battery fault features from time-frequency domains to improve sensitivity. • The clustering algorithm is used to realize the recognition of the fault battery. [ABSTRACT FROM AUTHOR]