The State of Charge (SOC) of lithium battery is one of the basic parameters of battery management system (BMS). The accurate estimation of SOC is the basis of BMS reliability and accuracy. In order to improve the estimation accuracy of SOC

an estimation method considering aging of lithium battery SOC was proposed. The Thevenin second-order model was selected as the equivalent model of lithium battery

and the parameters were identified and verified according to the actual data. Then

considering the influence of battery aging on model parameters and actual capacity

the improved Extended Kalman Filter (EKF) algorithm was added with total capacity calibration and forgetting factor

and the improved EKF algorithm was used to accurately estimate the SOC of the battery. Experimental results show that the accuracy of SOC estimation is greatly improved by adding capacity calibration and model aging genetic factors on the basis of EKF.