Study On The State Of Health And State Of Charge Of Electric Vehicle Power Battery

Battery management system as a key technology of electric vehicle has a very important position.State of Charge(SOC)and State of Health(SOH)are the key technologies of battery management system.Therefore,the study of SOC and SOH is of great significance for the development of electric vehicle.The purpose of this study is to establish a reliable battery model and study the estimation algorithm of SOC and SOH on the basis of model.The following is the main work of this article.This paper firstly introduces the working principle of lithium iron phosphate batteries commonly used as well as its main characteristics,the choice of 3.2V/3AH 26650 cells as experimental objects,the correlation characteristic experiment of the lithium iron phosphate battery,including the temperature experiment,the charge discharge rate,charge discharge cycle test experiment,the experimental results are analyzed.Battery model aspect,through the analysis and comparison of common battery model,Final choice two order Thevenin equivalent circuit model,parameter identification of the model on the basis of the HPPC experiments and the relationship function of SOC and OCV is obtained by MTALAB fitting tool.Finally,the parameters of the model are calculated and verified in the HPPC condition.The results show that the two order Thevenin circuit model can well simulate the dynamic characteristics of the battery.For the estimation of SOC,by comparing several commonly used SOC estimation algorithms,we choose the extended Calman filtering algorithm(EKF)and the unscented Calman filtering algorithm(UKF)to realize SOC estimation,and introduce adaptive covariance matching method to adjust the error.In order to verify the practicability and accuracy of the algorithm,a SOC estimation model based on the two order Thevenin model is established based on the UDDS operation mode as the experimental condition,and the UDDS current data collected from the experiment is used as the input of the model to simulate.By comparing the simulation results with the experimental results,it is determined that the unscented Calman filter algorithm can effectively realize the online estimation of SOC and make the estimation error converge within 3%.For the estimation of SOH,through the analysis of the characterization parameters of SOH,the battery internal resistance as the characterization of the SOH study is selected.Based on the study of SOC estimation,estimation using double extended Calman filter algorithm of SOC and SOH at the same time,the internal resistance of the battery as the characterization of the amount of SOH,the establishment of resistance estimation model,get the estimated value of the battery and SOC resistance in pulse discharge conditions,compared with the experimental measured results show that the double reference value.Calman filtering algorithm has a good estimation effect on cell SOH.