Study On The Correlation Of Discharge Curve Fitting Coefficient And Residual Capacity Of Different Capacity Lithium Batteries

Residual capacity estimation refers to the estimation of the residual capacity of a lithiumion battery based on the current voltage,current and other parameters,which is of great significance for battery management,battery design and battery research and development.The estimation of the remaining capacity of lithium-ion batteries is related to the state parameters of batteries,which include the state of charge(SOC),OCV-SOC curve and other factors.Therefore,this paper will focus on these parameters to estimate the residual capacity of lithium batteries as follows:(1)The internal structure and working principle of a ternary lithium-ion battery are discussed in this paper.Thevenin equivalent circuit model was selected as the equivalent model of lithium-ion batteries.Then,in order to determine the parameters of each component of the model,the off-line and online parameter identification algorithms are introduced.According to the experimental comparison,online identification has better prediction accuracy for the dynamic working conditions with real-time changes.The recursive least squares identification algorithm with an adaptive forgetting factor is used to identify the model parameters.By adding the adaptive formula of the forgetting factor,the rapidity,and stability of the online parameter identification algorithm are improved.(2)In order to solve the problem that it takes a long time to obtain the OCV-SOC curve in charge and discharge experiment,this paper designed a fast method to obtain the OCV-SOC curve based on the correlation of the fitting coefficient of the OCV-SOC curve.Based on the fitting relation of the same type of battery with a specific capacity,the OCV-SOC curve mathematical model is built,and the fitting relation between the voltage and SOC of other capacity batteries of the same type is directly obtained through the mathematical model.The experimental results show that the maximum error of the predicted value of OCV-SOC obtained by this method is about 1.5%.(3)Aiming at the influence of measurement noise under dynamic conditions,the residual capacity estimation error of lithium-ion battery is reduced and the residual capacity estimation accuracy of the battery is improved.The residual capacity estimation algorithm of exponential weighted fuzzy extended Kalman filter(FEKF)based on OCV-SOC curve correlation is adopted.Based on the OCV-SOC curve mathematical model,the battery voltage and other parameters of the remaining capacity estimation were obtained,and the measured noise was corrected by the fuzzy control algorithm according to the state of the system.In the simulation environment,the residual capacity estimation results are compared by three discharge conditions.The results show that the improved algorithm can effectively avoid the influence of noise and improve the accuracy of residual capacity estimation.