彭晓晗,马宏忠,许洪华,李晨,吴元熙,钱昆.基于振动的储能电池异常工况预警新方法[J].电测与仪表,2023,60(2):167-171. Peng Xiaohan,Ma Hongzhong,Xu Honghua,Li Chen,Wu Yuanxi,Qian Kun.A novel method of early warning for abnormal working conditions of energy storage batteries based on vibration[J].Electrical Measurement & Instrumentation,2023,60(2):167-171.
基于振动的储能电池异常工况预警新方法
A novel method of early warning for abnormal working conditions of energy storage batteries based on vibration
The vibration signal is introduced as a novel state parameter of the energy storage battery in this paper. By setting up the vibration signal detection platform of the energy storage battery, three operating conditions of normal charging, overcharging and charging are set up for the battery after external short circuit, and the vibration signal is collected. In order to completely reduce the characteristics of the vibration signal of the energy storage battery, Fourier transform and continuous wavelet transform are carried out to extract the amplitude and energy characteristics of the collected signal under different working conditions, and the following conclusions are obtained: (1) the vibration characteristics of the battery under different working conditions are different. (2) the characteristics of the two abnormal working conditions can be summarized as the main frequency change, the increase of vibration amplitude and the transfer of signal energy to the middle and high frequency band. The discovery of vibration characteristics of battery under abnormal working conditions is expected to provide a new research idea and reference for the condition monitoring and early warning of abnormal working conditions of energy storage batteries.
