Research On State Of Charge Estimation Of Lithium-Ion Battery Based On Improved Kalman Filter Algorithm

With the decreasing of non-renewable resources and growing environmental pollution,governments are actively seeking alternative energy solutions.The electric vehicles(EVs),known for their low carbon and energy conservation,have gained wide popularity in recent years.Lithium-ion batteries are considered as the most promising power source of EVs for their long cycle life,low self-discharge rate,high energy density,less pollution and security.To further commercialize the lithium-ion batteries,it is necessary to monitor the state information of the battery system by special means.Therefore,a battery management system(BMS)is designed to ensure the safe and reliable operation of the battery system.The estimation of state of charge(SOC)is the critically important part of BMS.The SOC has been widely used for the battery remaining mileage prediction in EVs.It serves a similar function to the fuel gauge of the oil-fueled vehicles.This paper takes a ternary lithium ion battery as the research object,and studies the estimation algorithm of SOC.The application of the extended kalman filter(EKF)algorithm in battery SOC estimation is emphasized.On the basis of knowledge of the lithiumion battery,the characteristics of existing models are introduced.The second-order RC(2RC)equivalent circuit model(ECM)is utilized to fit the actual lithium-ion battery.FDEKF algorithm and 2RC equivalent circuit model are established on Matlab/Simulink platform.Two conditions,constant current discharge(CCD)and Urban Dynamometer Driving Schedule(UDDS),are used to validate the FDEKF algorithm.The work and innovations of this paper mainly include:The FDEKF algorithm utilizes finite difference instead of partial derivative,and its accuracy is higher than that of the EKF algorithm.The finite difference algorithm is benefit to compute the partial derivative of nonlinear function,which can reduce the linearization error generated by the EKF.The FDEKF algorithm can reduce the computational load of controller in engineering practice,for without solving the Jacobian matrix.Comparing convergence rate and accuracy between the FDEKF and EKF algorithm,the results indicate the effectiveness of the proposed algorithm for SOC estimation in EVs.