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Optimal recharging framework and simulation for electric vehicle fleet

Tijdschriftbijdrage - Tijdschriftartikel

Electrical vehicles are considered sustainable transport alternatives as compared to conventional combustion engine vehicles due to their lower energy consumption and less pollutants production. The increased penetration of electric vehicles in the market depends upon technology to overcome the driving range barrier. That can be achieved by significantly planning the use of available charging stations. In this paper, a planning simulation model is presented which evaluates the feasibility of electric vehicles driving range when recharging is considered at home, at work or at quick charging stations in Flanders, Belgium. The proposed procedure plans a charging strategy for each electric vehicle so that entire scheduled tours of the individual can be executed successfully. The simulation starts by activating an agent for each electric vehicle that takes the daily schedule of the driver, registered charging requests at each charging station, and devises a charging strategy that may or may not require a detour to a charging station. Detouring to a charging station causes the time loss that result in the utility drop due to decreased participation in the planned activities. The charging station that leads to the minimum detour travel time, waiting time and recharging time is selected to minimize the time loss. The simulation uses a realistic travel demand predicted by an activity-based model. The results show the percentage of the population that can drive electric vehicle with charging only at home and/or work location; it also shows those who need a stop for recharging at a charging station. The results indicate the use of all charging stations over the day and also the waiting time as function of charging points at each charging station.
Tijdschrift: Future generation computer systems
ISSN: 0167-739X
Volume: 107
Pagina's: 745 - 757
Jaar van publicatie:2020
Trefwoorden:Quick charging station, Optimal charging, Electric vehicle, Time loss, Simulation model
BOF-keylabel:ja
IOF-keylabel:ja
BOF-publication weight:6
CSS-citation score:3
Authors from:Higher Education
Toegankelijkheid:Open