Lithium-ion battery SOC estimation study based on Cubature Kalman filter

In this paper, a state of charge (SOC) estimation method of Lithium-Ion battery is developed based on a cubature Kalman filter (CKF) supported by experimental data. Firstly, an equivalent circuit model and a fractional order model are established to evaluate the estimation accuracy of different models. Secondly, model parameters are identified through HPPC (Hybrid Pulse Power Characteristic) experiments based on the Sequential Quadratic Programming (SQR) method. Then, a CKF algorithm is used to eliminate the battery SOC under different battery models with no prior knowledge of initial SOC. The experimental results show that the proposed method can estimate the battery SOC with high accuracy and the fractional order model can achieve higher accuracy while it consumes more computing resources compared with EKF (Extended Kalman filter) algorithm.