Optimizing the Number of Electric Vehicle Charging Stations at Forecourts to Meet Demand

Due to the rapid increase in electric vehicle (EV) adoption, there is a pressing need for expanded charging infrastructure to accommodate this growth. The core challenge lies in balancing the number of EVs with the availability of charging stations to minimize wait times and enhance user satisfaction. This study employs a data-driven approach, utilizing hypothetical surveys of 100 EV users to gather insights into their experiences and expectations. Due to constraints on survey approval, assumptions were made regarding user responses. MATLAB-based artificial neural network (ANN) simulations were conducted to optimize the allocation of charging stations against the number of EV users. This method helps in predicting the required number of charging stations to effectively reduce charging wait times and improve overall user experience.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/upec61344.2024.10892374
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimizing the Number of Electric Vehicle Charging Stations at Forecourts to Meet Demand

Chun Sing Lai, Mohamed Darwish, Marwan Habashneh
Electric Vehicles and Infrastructure
article

Optimizing the Number of Electric Vehicle Charging Stations at Forecourts to Meet Demand

Chun Sing Lai, Mohamed Darwish, Marwan Habashneh
article en

Abstract

Due to the rapid increase in electric vehicle (EV) adoption, there is a pressing need for expanded charging infrastructure to accommodate this growth. The core challenge lies in balancing the number of EVs with the availability of charging stations to minimize wait times and enhance user satisfaction. This study employs a data-driven approach, utilizing hypothetical surveys of 100 EV users to gather insights into their experiences and expectations. Due to constraints on survey approval, assumptions were made regarding user responses. MATLAB-based artificial neural network (ANN) simulations were conducted to optimize the allocation of charging stations against the number of EV users. This method helps in predicting the required number of charging stations to effectively reduce charging wait times and improve overall user experience.

Brunel University of London (GB)
Openalex Percentile: Top 74%
Electric Vehicles and Infrastructure
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