Abstract
With the popularity of electric vehicles, lithium-ion batteries are widely used. As a temperature-sensitive component, the performance, life span, and safety of lithium-ion batteries are affected by their working temperature. Therefore, the monitoring of lithium-ion battery temperature is of great significance for electric vehicles. Currently, the temperature monitoring methods are mainly based on the measurement of battery surface temperature. It is difficult to obtain the more important internal temperature that reflects the actual electrochemical reaction status inside the battery. Herein, a prediction model for cylindrical 18,650 lithium-ion batteries is established to reveal the internal temperature under various boundary conditions. Firstly, T-type thermocouples are inserted into the battery to obtain the internal and surface temperature. The characteristics of the battery temperature variation at different discharge rates under different cooling conditions are analyzed in detail. Then, the calculation model of the battery internal temperature under different cooling modes is established by using the thermal network method. Finally, the accuracy of the prediction model is verified by the experimental data. The results show that the internal temperature at the positive terminal is higher than that in other parts. From the perspective of safety, this temperature can be used as a target parameter for the battery thermal management system and is also suitable as a warning parameter to monitor the battery thermal runaway. The battery internal temperature prediction model can achieve a high calculation precision based on the thermal network method. The absolute and mean square deviations can be controlled within 1.5 °C and 0.8 °C under the discharge rate of up to 1.5C and 1C pulse discharge. It provides high precision and reliable calculation method for the internal temperature prediction of power batteries in electric vehicles under daily driving with low discharge rates.
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