Adaptive Temperature Estimation for Lithium-Ion Batteries

In order to accurately estimate the temperature of lithium-ion batteries and solve the problem that the local temperature cannot reflect the overall average temperature, an adaptive temperature estimation method for lithium-ion batteries is proposed in this paper. Firstly, the experimental platform is built to obtain the open circuit voltage characteristic curve, the specific heat capacity and the entropy heat coefficient, which are necessary for modeling. Secondly, an adaptive temperature estimation method based on dual extended Kalman filtering and the principle of heat transfer theory is proposed under variable temperature environment. Lastly, the proposed method is verified by experiment under the Federal Urban Driving Schedule test. The results show that this method can estimate the temperature of the battery in real time during the operation of lithium-ion battery. The proposed algorithm can converge with different initial temperature, and the average error is only 0.2 °C. Therefore, the method proposed in this paper shows a strong robustness performance.