Research on Lithium-ion Batteries State of Charge Estimation based on Interactive Multiple-model Cubature Filter

Abstract

In this paper, an estimator Interactive multi-model cubature kalman filter (IMM- CKF) based on the combination of interactive multi-model algorithm (IMM) and cubature kalman filter (CKF) is applied to estimate the state of charge of lithium-ion battery. Firstly, two multiple models are set up to represent the different degree of parameter shift in the Lithium ion battery. Equivalent circuit methodology is used to construct the non-linear battery models. Secondly, the Interactive Multiple-Model Cubature Kalman Filter (IMM-CKF) and conventional Cubature Kalman Filter is used to estimate SOC of the battery. the numerical simulations and experiments have been done and the results show the effectiveness of interactive multi-model cubature kalman filter and its advantages over conventional methods with respect to estimation errors and variance. Compared with the traditional EKF, UKF and CKF algorithms, the IMM- CKF algorithm is found to yield better SOC estimation accuracy. The added computational cost of new estimator is acceptable.