基于振动的储能电池异常工况预警新方法

文中引入振动信号作为一种新的储能电池状态参数,通过搭建储能电池振动信号检测平台,对电池设置正常充电、过充和外部短路后充电三种运行工况,并采集其振动信号。为了完整还原储能电池振动信号的特征,对采集信号进行傅里叶变换和连续小波变换,提取不同工况下的幅值特征和能量特征,得到以下结论：(1)电池在不同工况下的振动特征存在区别；(2)两种异常工况的特征均可归纳为主频率改变、振动幅值上升和信号能量向中高频段转移。电池异常工况振动特征的发现,有望对储能电池的状态监测和异常工况预警提供新的研究思路和参考。

A New Method of Early Warning for Abnormal Working Conditions of Energy Storage Batteries Based on Vibration

In this paper, the vibration signal is introduced as a new state parameter of the energy storage battery. By setting up the vibration signal detection platform of the energy storage battery, three operating conditions are set up for the battery: normal charging, overcharging and charging 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.