| Title |
Electro-Thermal Modeling and RLS-EKF Based Co-Estimation of Battery SOC and SOT |
| Authors |
이성규(Seong-Kyu Lee) ; 손영우(Young-Woo Son) ; 이승현(Seung-Hyun Lee) ; 황상원(Sang-Weon Hwang) ; 김종훈(Jong-Hoon Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.8.1783 |
| Keywords |
Battery thermal model; Extended Kalman filter; Recursive least squares; State of charge; State of temperature |
| Abstract |
In this paper, a model is developed to simultaneously estimate the battery state of charge (SOC) and state of temperature (SOT). Initial electrical parameters are identified through hybrid pulse power characterization tests, and a recursive least squares (RLS) method is applied to update these parameters in real time based on current and voltage data. The updated parameters are coupled with a battery heat-generation model, and COMSOL and MATLAB/Simulink are integrated to validate the joint SOC?SOT estimation performance. Validation is conducted for two cells under UDDS and 1 C-rate capacity test conditions at an ambient temperature of 25°C. The results show that the proposed model reproduced SOC with low error and captured the overall SOT trend for both cells under the tested 25°C conditions, although transient mismatch was observed in some discharge intervals. These results support the feasibility of the proposed RLS-EKF-based joint SOC-SOT estimation framework under the tested conditions. |