Hardware in the Loop Demonstration of Battery Surface Temperature Prediction

Long-term continuous operation or high-rate charging and discharging processes generate a lot of heat in lithium-ion batteries. This can cause a rise in battery temperature, resulting in battery performance deterioration. The battery thermal management system (BTMS) increases the battery performance by keeping the temperature within an optimum range. In this study, a hardware-in-the-loop (HIL) system is developed for the verification of the designed temperature prediction algorithm. Since it is important to evaluate the performance of developed algorithms in real-world applications. In this work, a platform is developed to collect data from all sensors, store it on a computer, and then feed it into a temperature prediction algorithm. The MATLAB environment is used to compute and predict the surface temperature of the battery. To test the performance of real-time temperature prediction, normalized mean absolute error (NMAE) was chosen as the error metric. The demonstration of real-time temperature prediction is shown in a discharge test with 2C-rate and NMAE is computed as 1.7352 %.