The Optimal Location of the Electric Vehicle Infrastructure with Heterogeneous Batteries in the Highways

Mohammed Bourzik, Ahmed Elhilali Alaoui

2021

Abstract

The dynamic wireless charging makes the possibility of charging electric vehicles without contact and while it is in motion from the transmitters buried (segments and inverters) under the road. This technology is applied for homogeneous buses by the Korean institute of advanced technology (KAIST), called online electric vehicles (OLEV). Our contribution in this work is to study the problem of locating wireless charging infrastructure on a long route between origin O and destination S, with heterogeneous battery vehicles. On the first side, each type of vehicle requires its allocation of segments in the road because of the heterogeneity of batteries, which increases the number of recharge transmitters in the highway; for this purpose, we search to minimize the infrastructure cost by reducing the number of segments and inverters. On the other hand, the activity of a recharge segment may be helpful for one vehicle and useless for the other since each vehicle type has its characteristics (autonomy, puissance, battery capacity). For this reason, we aim to minimize the use of the recharge transmitters for each vehicle type. We propose to model the problem as a mathematical problem and to solve it by CPLEX optimizer for limited instances.

Paper Citation

in Harvard Style

Bourzik M. and Elhilali Alaoui A. (2021). The Optimal Location of the Electric Vehicle Infrastructure with Heterogeneous Batteries in the Highways. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 244-248. DOI: 10.5220/0010731900003101

in Bibtex Style

@conference{bml21,
author={Mohammed Bourzik and Ahmed Elhilali Alaoui},
title={The Optimal Location of the Electric Vehicle Infrastructure with Heterogeneous Batteries in the Highways},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={244-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010731900003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - The Optimal Location of the Electric Vehicle Infrastructure with Heterogeneous Batteries in the Highways
SN - 978-989-758-559-3
AU - Bourzik M.
AU - Elhilali Alaoui A.
PY - 2021
SP - 244
EP - 248
DO - 10.5220/0010731900003101