Forecasting the Temperature of BEV Battery Pack Based on Field Testing Data

Monitoring electric vehicles' battery situation and indicating the state of health is still challenging. Temperature is one of the critical factors determining battery degradation over time. We have collected more than 2.3 million discharging samples via a custom Internet of Thing device for more than one year to build a machine-learning model that can forecast the battery pack's average temperature in real-world driving. Our best Bi-LSTM model achieved the mean absolute error of 2.92 $$^\circ $$ C on test data and 1.7 $$^\circ $$ C on cross-validation for prediction of 10 min on the battery pack's temperature.