The Research Of Lithium-Ion Power Battery Model And SOC Estimation

With the intensification of global stone energy consumption,the price of non-renewable energy has risen steadily,and new energy technologies have become the focus of attention of all countries.New energy technologies have replaced fossil energy with their clean,clean and renewable advantages as the future development trend.At this stage,the country vigorously promotes the policy of new energy vehicles,and the sales of electric vehicles have steadily increased.Lithium-ion power batteries,as an important part of electric vehicles,have an important impact on the performance of electric vehicles.At this stage,the country vigorously promotes new energy automobile policies,and sales of new energy vehicles are steadily increasing.Lithium ion power batteries,as an important part of new energy vehicles,have important influence on the performance of new energy vehicles.Lithium-ion power battery SOC(charge state)estimation has an important impact on the charge and life of lithium-ion power battery,but the SOC estimation accuracy is not high,it is difficult to meet the accuracy requirements;At this stage,the common estimation of lithium-ion power battery methods mainly include ampere-hour integration method,discharge test method,open-circuit voltage method,etc.However,the accuracy of these methods is not high and the error is large.This paper uses extended Kalman filter algorithm to estimate SOC,and improves the algorithm.The improved algorithm has higher accuracy and accuracy of about 1%,which can effectively meet the SOC estimation requirements.Based on the relevant experiments,the article collects a large amount of experimental data,analyzes the voltage characteristics,internal resistance characteristics,and capacity characteristics of the lithium-ion power battery,and fully studies the characteristics of the lithium-ion power battery.This paper introduced the advantages and disadvantages of the electrochemical model,neural network model and equivalent circuit model of lithium ion battery in detail.The equivalent circuit model was selected as the model of lithium ion battery.Based on the equivalent circuit model,several common lithium-ion power battery models are analyzed in detail.Compared with other models,the PNGV equivalent circuit model has the advantages of high accuracy and low identification parameters.This article will improve the PNGV equivalent battery model as a lithium-ion battery model.By using the least squares method and particle swarm optimization algorithm to identify the parameters,the identification results were simulated and compared.The results show that the least squares method has higher accuracy and can more accurately reflect the internal characteristics of lithium ion battery.The paper establishes an improved PNGV equivalent circuit model and uses an extended Kalman filter algorithm(EKF)to estimate the SOC of Li-ion battery.The extended Kalman filter algorithm updates iteratively over the estimated values and has high stability.The extended Kalman filter algorithm is combined with the PNGV equivalent circuit.The simulation results are compared with the experimental data.The simulation shows that the extended Kal Mann filtering algorithm can accurately estimate the SOC of Li-ion power battery,and the average error is within 3%.The article analyzes the shortcomings of the Kalman filter algorithm in the process of SOC estimation,and improves the extended Kalman filter algorithm.Through simulation comparison,the SOC estimation of the improved extended Kalman filter algorithm is more accurate and the average error remains at 2%.Within.