ABSTRACT The relationship between state of charge (SoC) and open circuit voltage (OCV) is fundamental to SoC estimation in equivalent circuit models (ECMs). While its dependency on temperature and aging is recognized, the influence of real‐time capacity variations is often underexplored. This study investigates the impact of capacity degradation on the SoC–OCV relationship across different temperatures, aging levels, and OCV testing methods, using the CALCE and NASA battery datasets. Results show that when SoC is normalized by the degraded capacity, the SoC–OCV relationship remains nearly constant for SoC values above 20%. Leveraging this property, we propose a real‐time algorithm capable of simultaneously estimating SoC and capacity throughout the battery lifecycle. The algorithm also estimates state of health (SoH) by independently quantifying resistance and capacity related degradation. A first‐order ECM with a single resistor‐capacitor branch models battery dynamics, while Kalman filtering enables real‐time state updates. The method is validated under diverse conditions including partial and full discharges, varying temperatures, dynamic load profiles (e.g., US06, FUDS, BJDST, HPPC), and different aging states. Experimental results demonstrate robust performance, with SoC estimation errors within ±0.01 and capacity estimation errors within ±0.05 Ah, confirming the algorithm's effectiveness for real‐world battery management system applications.
Onur Kadem (Tue,) studied this question.