Developing a Model for Determining the Charging Station Location for Electric Vehicles

Electric vehicles, or EVs, have taken the spotlight in recent years in attempts to minimize the negative environmental effects associated with conventional modes of transportation. The location of charging infrastructure is an significant roadblock to promoting EV adoption; it demands careful planning in order to ensure the sustainability of EV use. Models like the Flow Capturing Location Model (FCLM) and Flow Refueling Location Model (FRLM) address this by considering operational constraints, system features, and uncertainties to provide effective solutions. In this study, Using MATLAB, R2020a the FCLM and FRLM were applied in Al-Karkh, Baghdad. When combined, the results revealed three key outcomes: identification of the nodes most frequently connected by traffic flows, with the shortest path method used to exclude paths that could not be utilized due to vehicle range limitations, and determination of the best nodes located along the shortest feasible routes dependent on the number of stations that the models chose.

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Publication Details

Journal
Sustainability
Published
2025-11-25
DOI
https://doi.org/10.3390/su172310562
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Developing a Model for Determining the Charging Station Location for Electric Vehicles

Halit Özen, Sura Hussein Mijdim AL HAMEEDAWI
Sustainability
Electric Vehicles and Infrastructure
article

Developing a Model for Determining the Charging Station Location for Electric Vehicles

Halit Özen, Sura Hussein Mijdim AL HAMEEDAWI
article en

Abstract

Electric vehicles, or EVs, have taken the spotlight in recent years in attempts to minimize the negative environmental effects associated with conventional modes of transportation. The location of charging infrastructure is an significant roadblock to promoting EV adoption; it demands careful planning in order to ensure the sustainability of EV use. Models like the Flow Capturing Location Model (FCLM) and Flow Refueling Location Model (FRLM) address this by considering operational constraints, system features, and uncertainties to provide effective solutions. In this study, Using MATLAB, R2020a the FCLM and FRLM were applied in Al-Karkh, Baghdad. When combined, the results revealed three key outcomes: identification of the nodes most frequently connected by traffic flows, with the shortest path method used to exclude paths that could not be utilized due to vehicle range limitations, and determination of the best nodes located along the shortest feasible routes dependent on the number of stations that the models chose.

SustainabilityVol. 17(23)
Yıldız Technical University (TR), Istanbul Technical University (TR)
Openalex Percentile: Top 64%
Electric Vehicles and Infrastructure
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