Abstract
The number of electric vehicles has increased significantly in recent years. The battery is its power source, so to estimate its state of charge (SOC) is meaningful. The extended Kalman filter (EKF) algorithm and the unscented Kalman particle filter (UKF) are integrated through analytic hierarchy process and Euclidean distance method as the proposed distribution function of the particle filter (PF) algorithm which is developed into algorithm of improved particle filter. The fusion algorithm is applied to estimate the SOC of the third-order Thevenin model of batteries. Experimental results show that the SOC estimation accuracy of the fusion algorithm is better than that of EKPF and UPF.
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