Research On Joint Estimation For Model Parameters Identification And SOC Of Li-ion Battery Of Electric Vehicle

In recent years,due to energy crisis,environmental pollution and many other factors,electric vehicles have once again become the focus of world attention.As the core part of electric vehicles,power batteries have also become one of the hot topics in current research.The state of charge(SOC)is an important parameter of the battery and is of great significance to the battery management system.Accurate SOC value avails to increase the battery life and ensure the safety of the electric vehicle.This paper makes the following research on the online real-time identification of lithium-ion battery parameters and the improvement of SOC real-time estimation accuracy.Through the research on the factors that affect the accurate estimation of the battery SOC,several comparatively well-developed SOC estimation algorithms are compared and analyzed.It is proposed that the multiple algorithms be used in combination to estimate the state of charge of the lithium-ion battery in real time.The battery model is used as the basis for the realization of the algorithm,which requires a higher simulation accuracy.This paper compares the advantages and disadvantages of the common battery model's topology and establishes a second-order RC network equivalent circuit model suitable for the power lithium battery.Based on the model,the off-line parameter identification method is studied.According to the identification result,the RC equivalent circuit simulation model is built during the environment of SIMULINK,and the current under several common operating conditions is used as the input of the model to verify the accuracy of the model.During the actual work of electric vehicles,there are many influence factors lead to the relevant parameters of the power battery working cannot keep constant.So this paper focuses on the online identification method of lithium battery parameters.During the process of online identification,due to the problems of data saturation and the complexity of dynamic operating environment,this paper uses adaptive multiple forgets factor recursive least squares method to realize the parameter online real-time identification process of equivalent circuit model and writes the identification procedure in MATLAB environment to verify the algorithm program.Secondly,the SOC estimation algorithm of Li-ion battery is studied.Due to the nonlinear characteristics of Li-ion battery,this paper uses Ah-total integration method,extended Kalman filtering algorithm and joint algorithm combined with parameter identification to perform the battery state of charge separately.The final simulation results show that the joint algorithm not only has strong robustness,but also has high precision for the SOC estimation results.Finally,battery electric vehicle model built by the simulation software ADVISOR and set parameters of the model.Then simulation tests are performed under the combined driving conditions of CYC_ECU_EUDS and CYC_NYCC.According to the battery current,voltage and other information to achieve real-time estimation of the battery SOC by the joint algorithm.To verify the effectiveness and accuracy of the joint algorithm under dynamic conditions.