Research On State Of Health Estimation Of Lithium Ion Batteries Based On Time Domian Electrochemical Impedance Spectroscopy Measurement

With the increasing application of lithium-ion batteries,lithium-ion batteries as the system's energy supply is the key to the entire system.Therefore,it is very important to monitor the battery and accurately estimate its performance and state of health.The research of this project is based on an electrochemical impedance spectroscopy time domain measuring method.A lithium ion battery equivalent circuit impedance model is established,and electrochemical impedance spectroscopy(EIS)as an effective tool is used to study the state of health estimation of lithium ion batteries.The work of this project is as follows:First,a time domain measuring method of impedance spectroscopy based on Fast Fourier Transform(FFT)is studied on the measurement of impedance spectrum of the battery.The multi-sine wave current is used as the excitation signal and the battery response signal is collected,EIS is obtained by performing data processing through FFT.Compared with the traditional frequency sweeping measuring method,this method can greatly reduce the time required for measurement and ensure certain accuracy,and has the advantages of simple and inexpensive equipment.Second,combined with the electrochemical principle,an equivalent circuit impedance model of a lithium ion battery is established.Based on the simplification of the single-particle model of the electrode,the Faraday process,the electric double layer effect,and the electrochemical process such as the SEI film are considered.The equivalent circuit impedance model of the positive and negative electrodes is deduced to obtain the equivalent circuit impedance model of the whole battery.The parameters of the model are identified by the genetic algorithm.Compared with the most commonly used Randles equivalent circuit model,it is proved that the model has higher fitting accuracy.Finally,the battery aging test was designed and the model parameters were selected as the health characteristic parameters to estimate the battery health status.The aging test under two different magnifications was designed and five parameters were selected as the health characteristic parameters in the aging process.The BP neural network algorithm was used and battery capacity estimation was achieved.The health status of the battery is further defined by the area enclosed by the five health feature radar charts,and the battery health status is comprehensively evaluated from the perspective of the internal reaction process.