State of Charge Estimation of Lithium-ion Batteries Based on An Adaptive Cubature Kalman Filter

An adaptive cubature Kalman filter is proposed in this paper to estimate the state of charge (SOC) of a lithium-ion battery. Firstly, a second-order RC equivalent circuit model is constructed to describe the dynamic characteristics of a lithium-ion battery. Secondly, we design a linear Kalman filter and a cubature Kalman filter to achieve the adaptive estimation of SOC, model parameters and the coefficients in the measurement equation. Thirdly, the noise covariance matrices are adaptively adjusted in order to further improve the estimation accuracy of the proposed algorithm. Finally, the estimation accuracy and adaptability of the algorithm proposed in this paper are verified by different experiments.