Abstract
Electric vehicles (EVs) are vital in achieving a sustainable and eco-friendly transportation system. However, the transition to EVs faces significant challenges, mainly range anxiety, which is the fear of running out of battery power without access to charging facilities. Identifying locations for Electric Vehicle Charging Stations (EVCS) to address this issue and promote EV adoption is crucial, especially for intercity travel. The study proposes a three-stage solution methodology utilizing the Variable Transportation Demand Model (VTDM) established for nationwide transportation planning. The proposed approach includes identifying EVCS locations, with path-based traffic demands derived from the VTDM’s generalized cost-based shortest path methodology for different trip purposes. The proposed approach was validated using real-world big data from the Türkiye National Transportation Master Plan (TNTMP). The results revealed that 2,161 charging stations are required to ensure uninterrupted travel throughout the network. Furthermore, the study identifies a discrepancy in the availability of charging station infrastructure across different regions, with the majority of new facilities concentrated in the eastern region of Turkey. Addressing this infrastructure gap is crucial for accelerating the adoption of electric vehicles (EVs), reducing carbon emissions, and promoting sustainable transportation systems at the national level.
Original language | English |
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Pages (from-to) | 36348-36358 |
Number of pages | 11 |
Journal | IEEE Access |
Volume | 13 |
DOIs | |
Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Authors.
Keywords
- charging station location problem
- Electric vehicles
- heuristic algorithm
- variable transportation demand model