Analysis and Estimation of Internal Temperature Characteristics of Lithium-Ion Batteries in Electric Vehicles

Abstract

To avoid thermal runaway in battery packs, it is necessary to estimate the internal temperature. Herein, the relationship between measurable electrical parameters and adjustable electrochemical parameters is first studied. Then, adjustable electrochemical parameters at different temperatures are rapidly calibrated. Based on this, an electrochemical-thermal coupling model is proposed. Second, the internal temperature field distribution is analyzed by the coupling model. It is found that the gradient of the radial temperature distribution is greater than that in the axial direction. Third, a radial thermodynamic reduced-order model is developed. The thermal parameters are calculated by the combination of the direct method and Variable Forgetting Factor Recursive Least Square (VFFRLS) algorithm. Finally, an internal temperature estimator based on the Kalman Filter algorithm is produced. Results show that the maximum estimated error is only 1.57 K under different working conditions. Furthermore, the results also validate the feasibility of thermal parameters obtained algorithm.