Effects of Battery Model on the Accuracy of Battery SOC Estimation Using Extended Kalman Filter under Practical Vehicle Conditions Including Parasitic Current Leakage and Diffusion Of Voltage

Abstract

Accurate estimation of battery State of Charge (SOC) is a crucial factor for the safe and efficient usage of the batteries in hybrid electric vehicles. The combined method of Coulomb counting and Open circuit Voltage (OCV) is already under practical usage for the estimation of battery SOC, but the methods have significant error when there is parasitic current leakage (dark current) or short rest period. Thus, Extended Kalman Filter (EKF) is one of the battery SOC estimation methods used to overcome such drawbacks. And, most importantly, due to structural dependency of EKF upon battery model, the battery model used for the EKF contributes significantly to the accuracy of EKF. Thus, in this paper, 3 types of battery Equivalent Circuit Models (ECMs) including second order RC model, first order RC model, and R model are compared under practical vehicle driving conditions. To simulate the vehicle driving condition, a micro Hybrid Electric Vehicle (micro-HEV) is modeled and simulation is conducted under NEDC condition.