Selecting an Optimal Single-Temperature Battery Model for Robust State-of-Charge Estimation across Thermal Conditions

This paper investigates the effect of ambient temperature on the accuracy of state-of-charge (SoC) estimation in lithium-ion batteries using the Extended Kalman Filter (EKF). Experimental evaluations were conducted at three distinct temperatures—۵°C, ۲۵°C, and ۴۵°C—representing low, nominal, and high thermal conditions. Results reveal that battery performance and SoC estimation accuracy significantly depend on temperature, with ۲۵°C providing the most stable electrochemical behavior and lowest estimation error. A dual-cell equivalent circuit model is employed to simulate the battery dynamics, and EKF is utilized as a real-time estimator due to its robustness in handling non-linear systems. Additionally, a thermally stable SoC operating range between ۷۰% and ۳۰% is identified, where the battery exhibits a reliable and predictable response across all tested conditions. These findings underline the importance of incorporating temperature effects into battery modeling for improved performance and safety in practical applications.

کلیدواژه ها:

Lithium-ion battery ، State-of-Charge ، Temperature dependence ، Extended Kalman Filter ، Dual-cell equivalent circuit model ، Thermal behavior