The quick and accurate estimation of the state of charge (SOC) of lithium-ion battery is one of the key technologies of battery management system. In view of this nonlinear dynamic system of lithium battery, through the test and analysis of lithium-ion battery hysteresis characteristics, the second-order RC hysteresis model was established, and the cubature kalman filter algorithm was used to estimate the battery state of charge. The experiment results show that the battery model can essentially predict the dynamic hysteresis voltage behavior of the lithium-ion battery and cubature kalman filtering algorithm can maintain high accuracy in the estimation process.