State-of-Charge Estimation Using an EKF-Based Adaptive Observer

Abstract

Lithium-ion batteries are used to store energy in electric vehicles. State of charge (SOC) is an important quantity of the battery cells that need to be estimated using limited measurements. In this paper, SOC estimation via an electrochemical model, a physics-based model, is considered. For lithium iron phosphate cells, a variable solid-state diffusivity model provides significantly more accuracy, but this complicates the model further. A previously obtained, simplified but still a physics-based model is used in this paper. An extended Kalman filter (KF)-based adaptive observer is designed via a low-order approximation of this electrochemical model. The predictions of the estimator are compared with the experimental data in simulations. The simulations are efficient and more accurate than a standard KF.