Core temperature estimation of lithium-ion battery for EVs using Kalman filter

In this paper, an estimation scheme of the battery core temperature based on Kalman Filter (KF) is presented to guarantee the battery safety and discuss the temperature non-uniformity inside the cell. Assuming that the temperature distribution of a cell is simplified into three areas for reducing the calculation amount, a battery pack reduced-order model (ROM) is first developed to achieve real-time estimation of the core temperature of each cell, considering cell inner electrical resistance varying with temperature. Next, recursive least square (RLS) algorithm is adopted to identify the unmeasurable parameters of the battery ROM. Then, the battery pack ROM is validated using Computational Fluid Dynamics (CFD) to simulate the thermal behavior of the battery. Finally, a core temperature estimation scheme using KF is verified. Simulation results suggest that the errors of cell core temperature at different velocities of inlet air are less than 1 K. Meanwhile, the maximum temperature non-uniformity 6.55 K and the minimum temperature non-uniformity 1.13 K are observed in the eighth and first cell respectively at three inlet air velocities of 0.1 m/s, 3 m/s and 7 m/s