Enhanced OCV Estimation in LiFePO4 Batteries: A Novel Statistical Approach Leveraging Real-Time Knee/Elbow Detection

The rapid advancement of electric vehicles (EVs) and renewable energy storage systems has significantly increased the demand for reliable and efficient battery technologies. Lithium iron phosphate (LFP) batteries are particularly suitable for these applications due to their superior thermal stability and long cycle life. A critical parameter in optimizing the performance of LFP batteries is the open-circuit voltage (OCV), essential for accurate state of charge (SoC) estimation. The accurate determination of the OCV is challenging due to relaxation effects post-charging/discharging, causing voltage changes for up to 24 h or even more until stabilization. This paper presents a novel statistical model for OCV estimation that employs an online observer to detect the knee/elbow point in the voltage relaxation curve. By utilizing the voltage at the knee/elbow point and the initial voltage, the model accurately computes the OCV at the stabilization point. The proposed method, validated with extensive experimental data, achieves high accuracy, with a computed error of less than 0.26% for charging and under 1.2% for discharging.