Driving Range Prediction of Electric Vehicles: A Machine Learning Approach
Shahid A. Hasib, Dip Kumar Saha, Saidul Islam, Mahib Tanvir, Md. Shahinur Alam
Abstract
Due to the immense progress of green energy technology, the popularity of electric vehicle (EV) is increasing day by day. The rapid transition from internal combustion engine-based vehicle to battery-driven vehicle creates another issue that is limited storage capacity of batteries. Researchers are working hard to improve the storage capacity of battery through use of advanced materials. Meanwhile, the accurate prediction of driving range of EV has become a topic of interest for the researchers. In this paper, multiple regression machine learning algorithms are used to predict the electric vehicle range. Among the models, Multiple Linear Regression (MLR) gives the best R squared value of 0.973 and the lowest RMSE value of 39.67 in predicting the EV range. The result is compared with other machine learning models.