Electric vehicle battery consumption estimation model based on simulated environments

@Article {
title = {Electric vehicle battery consumption estimation model based on simulated environments},
journal = {International Journal of Vehicle Information and Communication Systems},
pages = {309-333},
volume = {9},
keywds = {
battery estimation; data set; deep learning; electric vehicle; energy consumption; simulation
}
abstract = {

Governmental policies are promoting using Electric Vehicles (EVs) to reduce carbon emissions and make transportation more energy efficient. Car manufacturers are putting much effort into making reliable EVs. However, consumers still have to deal with the lack of enough infrastructure and an immature technology readiness level. In order to have an accurate battery range prediction and lessen these issues, this research proposes an energy consumption estimation model based on factors related to battery consumption during a trip. As part of the process, Simulation of Urban Mobility (SUMO), a well-known traffic simulation tool, has been used to run many simulations, produce a heterogeneous data set and train the model with a neural network. The results show an accurate battery range forecast, with a coefficient of determination of 0.91. This model can determine trip consumption considering conditions that vehicle manufacturers’ reference consumption values do not.

}
doi = {10.1504/IJVICS.2024.139759},
date = {2024-01-01},
}