Electrochemical Modeling Of Lithium Ion Battery Based On Electrical Double Layer And SOC Estimation

The power battery system is one of the most important systems of new energy vehicles.It has great influence on the power and safety of the vehicle.Lithium-ion batteries have become the most widely used power battery for vehicles due to its excellent performance.For new energy vehicles,besides searching for highperformance electrode materials,it is also important to develop Battery Management System(BMS)for power batteries to prevent the self-ignition and explosion of batteries in some extreme conditions.State of Charge(SOC)estimation of the battery is the basis of the BMS and has a significant impact on the energy management of the vehicle.An accurate SOC estimation is conducive to use the battery adequately,extend battery life and improve applied safety.Compared with the equivalent circuit model,the electrochemical model is developed based on the electrochemical reaction mechanism,so it can essentially reflect the relationship between the external parameters of the battery and the internal electrochemical reaction.Therefore,the accuracy of prediction and SOC estimation for the battery is higher.This paper presents an electrochemical model based on the effect of the electrical double layer structure(EDL)in the electrochemical reaction process of lithium-ion battery,which can characterize the lithium-ion battery accurately.A SOC estimation algorithm based on the simplified electrochemical model is established.Research of this paper may provide some certain reference for the application of electrochemical model in BMS to some degree.The main research work is as follows:Firstly,the electrode solid-phase and electrolyte liquid-phase of lithium-ion power battery are modeled using electrochemical theory.The influence of the electrical double layer on the over-potential of the battery is mainly considered,and the three-parameter parabola method is used to simplify it.On this basis,the system structure of electrochemical model is established,and the electrical double layer model of the lithium-ion power battery is deduced.Secondly,in order to improve the accuracy of the model,in the light of characteristic of electrical double layer model,a parameter identification method on the basis of genetic algorithm is presented.Six groups of electrochemical parameters in the lithium ion battery are identified according to the data from 0.1C constant current charging experiment terminal voltage data and EDL model terminal voltage,using A123 lithium iron phosphate battery as the research object.The accuracy of the model was verified through experiments.Based on these,open circuit voltage of positive electrode curves of the battery are both fitted.Then,the EDL model of lithium-ion battery was built in MATLAB/Simulink,and the change process of lithium ion concentration and EDL potential in the solid phase of the battery are analyzed,which deepen the understanding of the battery characteristics.Accuracy of the EDL model is verified by comparing the terminal voltage obtained from experiments and EDL model under constant current charging and discharging conditions,variable current conditions and NEDC operation conditions respectively.Errors and sources are analyzed,too.Besides these,the accuracy of the electrical double layer and the single particle model is compared under constant current charging and discharging conditions.Finally,based on the EDL model of lithium ion power battery,SOC of the battery in the electrochemical model is redefined,and the SOC estimation method of battery is designed by using the extended Kalman filter algorithm.Accuracy of the method is proved by experiments under single-cell 1C pulse discharge condition and the vehicle NEDC condition,and the initial SOC error can also be corrected using the extended Kalman filter algorithm based on the EDL model.