From Motor to Battery: A Digital Twin Model of Electric Vehicles

Abstract

Batteries play a vital role in electric vehicles (EV) because batteries are the only source of power for EV. To ensure the safe and normal driving of EV, we need to monitor batteries in EV. To achieve the above purpose, it is necessary to install a large number of sensors in the battery management system (BMS). However, more sensors lead to more problems. For example, the installation of more current sensors will compress the interior space of EV, incur higher error rates and increase the manufacturing cost of EV. Moreover, whether the sensor can work properly is highly susceptible to environmental factors. To solve the above problems, this paper proposes a digital twin model for predicting battery current using motor torque and vehicle speed. We establish a regression model between motor torque and current through the KNN algorithm. Experiments show that the prediction accuracy of the digital twin models in actual situations has reached an astonishing 95%.