Abstract: The battery management system can reflect the operation status of lithium batteries, and one of its core tasks is to estimate the state of charge of lithium batteries. To address the issue that the actual value of SOC cannot be directly obtained, a series of improvements are first made to the extended Kalman filtering to overcome its difficulty in directly processing nonlinear systems. Then, a second-order equivalent circuit model is established and the L-M algorithm is utilized to identify the parameters of lithium batteries. Finally, after completing the parameter identification of lithium batteries, the improved EKF algorithm is used to estimate the SOC. The results show that the estimated SOC values have a small error compared to the actual values, and this method can accurately estimate the SOC of lithium batteries.