In the state-of-charge estimation of power battery, the traditional Extended Kalman Filter (EKF) ignores high-order terms and Particle Filter (PF) suffers from particle degradation and loss of diversity during the resampling process. To address this issue, this paper proposed the improved Mixed Kalman Particle Filter (MKPF) algorithm. Firstly, the extended Kalman filter was used to generate the state estimate of the system, and then the unscented Kalman filter was used to repeat the process. The state estimates obtained by the extended Kalman filter and the unscented Kalman filter were used together as the particle filter proposal distribution, and value sorting was used to determine the survival of the fittest particles. Simulation and experimental results show that the maximum error of SOC estimate by the proposed algorithm is 1.2%, which is better than the estimation accuracy of the existing PF, EKF, and UKF algorithms on SOC.