Lithium Battery SOC Estimation Method And Implementation Based On Second-order Kalman Filter

As the energy crisis and environmental problems are increasingly serious,governments and auto enterprises around the world pay more and more attention to the development of clean,efficient and pollution-free electric vehicles.The battery technology,which is one of the three core technologies of electric cars,is the main factor limiting the development of electric vehicle,and its state estimation is related to energy management,cycle life,cost of use and safety.Therefore,the accurate estimation of the power battery SOC is of great significance to improve the battery life and vehicle performance.In this paper,lithium-ion batteries as the research object,using the unscented Kalman filter algorithm(UKF)to estimate the SOC of the battery,and achieved good results.Firstly,the related experiments were designed.Based on the experiments,the basic characteristics of lithium-ion batteries were analyzed,and the effects of different discharge rates on the battery capacity,internal resistance,and open-circuit voltage were studied.Based on the analysis of several equivalent models commonly used in batteries,the second-order Thevenin model was selected as the equivalent circuit model of the battery.According to the characteristics of the model,a hybrid pulse power characteristic(HPPC)cycle experiment is used.The mathematical relationship between the parameters in the second-order model and the SOC is fitted using the cftool tool in Matlab.The simulation model is built in Matlab/Simulink,and different cycles are used.The battery model was simulated and verified by operating conditions.The error between the model output voltage and the battery's true value was compared.It was verified that the second-order Thevenin model has higher accuracy and can better reflect the dynamic characteristics of the battery.Based on the second-order Thevenin equivalent circuit model and its parameter identification results,the UKF algorithm was used to estimate the battery SOC.The UKF program was written in Matlab/Simulink,and the calculation result of the ASM calculation was used as the reference value.The HPPC experimental data was brought into the UKF program.The algorithm was verified under three conditions:accurate initial value,model parameter error,and initial value error.This verified the feasibility of UKF estimating SOC.