Study On Aging Mechanism And Modeling Of Power Lithium-ion Battery For Electric Vehicle

As the core component of power source and energy storage construction of new energy vehicles,the importance of promoting its rapid development,safe and effective development and application is self-evident.However,the estimation of state of charge and aging study of lithium-ion batteries,as two major problems restricting its development,have not been effectively solved so far.Aiming at the problem that it is difficult to accurately estimate the state of charge of lithium battery and the performance degradation caused by battery aging,this paper deeply studies the charging and discharging characteristics and aging mechanism of the battery,and puts forward a fractional-order battery model with hysteresis characteristics,and uses multiple regression algorithm to find out the regular relationship between battery aging and key parameters.Firstly,the battery characteristics of the studied battery are tested,including the relationship curves between battery voltage and state of charge at different temperatures and different rates.Aiming at the battery hysteresis phenomenon,the main loop hysteresis experiment,small loop hysteresis experiment and the temperature dependence,path dependence and state-of-charge dependence of hysteresis voltage are studied.Based on the experimental data,a battery hysteresis voltage model is proposed,and the maximum error of the model is 17 m V.Based on hysteresis model and fractional equivalent circuit model,a fractional equivalent battery model is established.Based on the fractional derivative theory and extended Kalman principle,a fractional extended Kalman algorithm is derived,which can accurately and effectively estimate the battery state of charge,and the estimation error is about 2%.Furthermore,the battery cycle aging experiment was carried out,and the changing rules of battery cycle times,aging internal resistance,constant current charging time and constant voltage charging time under different health conditions were analyzed.Based on the aging experimental data,a multiple regression algorithm is established.The model can accurately reflect the change rule of aging degree and aging characteristic parameters,and the maximum model error is 3%.