State-of-charge Estimation For Lithium-ion Battery Using A Combined Method

With the increasing global energy and environmental crisis,the electric vehicles have been widely developed.Lithium-ion battery,as a highly efficient clean green energy,has become the main power source of electric vehicles,and its performance is the key to the performance of the vehicle factor.The battery management system(BMS)manages the electric vehicle charging and discharging as well as the power optimization correctly and effectively.It can ensure that lithium ion batteries work in a safe range,which provides an important basis for the rational use and maintenance of electric vehicles,and improves the mileage and service life of electric vehicles.The core of the battery management system is to estimate the charge state of the battery(SOC)accurately,and the accurate estimation of the lithium ion state can avoid the overcharge and over discharge of the battery and prolong the service life of the battery.But the SOC cannot be directly measured,and it can only be estimated through the battery voltage,charge/discharge current and other external parameters.These parameters are easily influenced by the temperature of the battery and other working conditions,which increase the difficulty of forecasting SOC.The battery model is the link of the electrical characteristics of external and internal battery cell electrochemical reaction,and it is a prerequisite for the prediction of SOC.The parameter of Lithium-ion battery is effected by environment and load characteristics.The battery model is highly nonlinear.Based on the study of the various battery model,the hybrid electrochemical model is used in this paper.And forgetting factor least squares method is proposed for identifying the battery model’s parameters,the experimental results verify the battery model has high precision and good dynamic response to the battery and static characteristics.Based on UKF algorithm and PF algorithm,the paper proposes a new hybrid algorithm.The hybrid method is applied to estimate SOC of lithium-ion battery.By comparison with EKF,UKF and PF,the proposed algorithm has the superiority performance in accuracy,real-time and robustness advantages.