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

Chun Chang, Qiyue Wang, Jiuchun Jiang, Yan Jiang and Tiezhou Wu

Energy, 2023, vol. 278, issue PB

Abstract: 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.

Keywords: Power battery; Fault diagnosis; Wavelet time-frequency diagram; Image entropy; Clustering (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223013142

DOI: 10.1016/j.energy.2023.127920

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