SOC estimation and simulation of electric vehicle lead-acid storage battery with Kalman filtering method

摘要

Low carbon economy being the theme of economic development, the progress of electric vehicle is emphasized with policies in China. Storage battery, functioning as the power source of electric vehicle, has always been confining the progress of electric vehicle. This paper, based on the charge-discharge characteristics and their relations with remaining power, builds an equivalent Randle circuit model of lead-acid battery, and presents that the remaining power of the storage battery (SOC) could be continuously predicted and estimated. By using the Kalman filtering method, and combining the overall model made by MATLAB-simulink tool with the Kalman filtering method, the estimation and simulation is carried out. The result shows that the Kalman filtering method has advantages of efficiency and accuracy over other filtering methods in terms of estimating the SOC of storage battery.