State of Charge Algorithm Considering Open Circuit Voltage of LiFePO4 Battery Cells for Battery Energy Storage System

Lithium iron phosphate (LFP) batteries are increasingly adopted in electric vehicles (xEVs) and battery energy storage systems (BESS) due to their thermal stability, safety, and cost-effectiveness. Despite these advantages, the inherently low electrical conductivity and flat charge-discharge voltage profile of LFP batteries present significant challenges for accurate state estimation. To address these limitations, this study employs a Sigma-Point Kalman Filter (SPKF), which demonstrates superior performance compared to the conventional Extended Kalman Filter (EKF) in handling nonlinear system dynamics. Furthermore, to account for the hysteresis behavior characteristic of LFP cells, quasi-open circuit voltage (qOCV) measurements are utilized. A Dual Sigma-Point Kalman Filter (DSPKF) is proposed to enhance the estimation of both state of charge (SoC) and hysteresis states. The experimental results validate the effectiveness of the proposed method, offering a high-precision state estimation framework that improves the reliability and performance of LFP batteries in xEV and BESS applications.