Real-time Fault Diagnosis Method of Battery System Based on Shannon Entropy

Ensuring the safety of the power battery is of great significance to make the diagnosis more effective and predict the occurrence of fault because power battery is one of the key technologies of electric vehicles. In this paper, decomposition with 3 layers developed by Daubechies is used to deal with the collected noisy voltage signal of lithium-ion battery from the experiment, which can get relatively smooth voltage signal and eliminate noise interference. A diagnostic method of using Shannon entropy is proposed to process measured data after wavelet transform, and we get a relatively reasonable parameters l = 50 with analysis of interval parameters l. After the 10th cycle, fault of NO.1 cell can be accurately found through calculating Shannon entropy of charge and discharge cycles. The method proposed in this paper can achieve real-time diagnosis but it is easily affected by interval parameter l.