A Digital Twin Model for the Battery Management Systems of Electric Vehicles

Batteries play a crucial role in electric vehicles since they are the only power sources of the vehicles. In order to guarantee that batteries can work efficiently and safely, battery management systems (BMS) are employed to measure, estimate and regulate battery states during the operation of electric vehicles. To do that, numerous voltage, current, and temperature sensors are required to be installed in the BMS. However, a large number of sensors may lead to some problems, e.g., high cost, reduced space, low efficiency, and high failure rates. To address these challenges, in this paper, a digital twin paradigm is proposed for the BMS to estimate and predict the battery states with only a voltage sensor. A multi-linear regression algorithm is utilized to build the regression model between battery voltage and the other variables. Experiment results show that the proposed digital twin model achieves over 90% prediction accuracy in practical applications.