SOC estimation of LiPB batteries using Extended Kalman Filter based on high accuracy electrical model

Abstract

This paper proposes a SOC (State-of-charge) estimator of batteries using the Extended Kalman Filter (EKF). EKF can work properly only with accurate model. Therefore, this paper includes high accuracy electrical battery model for EKF state. The modeling is focused on high-capacity LiPB batteries. The battery model is extracted from single cell of LiPB 40 Ah, 3.7 V. The dynamic behavior of single cell battery is modeled using a bulk capacitor, two series RC networks and a series resistance. The voltage in bulk capacitor represents OCV (Open Circuit Voltage) related to SOC value. EKF is employed to estimate the OCV, and then OCV is converted to SOC value. EKF is tested with experiments data obtained by MACCOR battery tester. EKF is improved with single varying parameter of bulk capacitor which follows the SOC value. The test of estimator algorithm is done for full region of SOC. The test results show the error of estimation can reach max 5%SOC at some points.