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Locating charging infrastructure for freight transport using multiday travel data

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  • Fu, Jiali
  • Nåbo, Arne
  • Bhatti, Harrison John

Abstract

Vehicle electrification has shown the potential to reduce environmental impacts and greenhouse gas emissions from the transport sector. As electric vehicles (EVs) become increasingly prominent, the efficient placement of charging infrastructure poses a complex challenge that demands careful consideration. This paper delves into the investigation of how travel and parking patterns, derived from empirical data on freight vehicles, influence the optimal distribution of charging infrastructure across the freight network. This paper presents a node-based approach to optimize the allocation of charging infrastructure tailored explicitly for freight transport. The study identifies optimal locations for operator-owned charging infrastructure by leveraging GPS-based data collected from a fleet of freight vehicles operating in the greater Gothenburg metropolitan area. This research aims to enhance our understanding of the charging infrastructure requirements inherent in the freight transport system and provide decision support to logistics companies contemplating the shift from conventional fossil fuel vehicles to electric freight vehicles. The proposed model holds the potential for seamless adaptation to diverse freight transport systems, offering valuable insights to expedite the transition toward fossil-free freight transport on a broader scale.

Suggested Citation

  • Fu, Jiali & Nåbo, Arne & Bhatti, Harrison John, 2024. "Locating charging infrastructure for freight transport using multiday travel data," Transport Policy, Elsevier, vol. 152(C), pages 21-28.
    • Handle: RePEc:eee:trapol:v:152:y:2024:i:c:p:21-28
    DOI: 10.1016/j.tranpol.2024.04.007
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    References listed on IDEAS

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    1. Ramesh Chandra Majhi & Prakash Ranjitkar & Mingyue Sheng & Grant A. Covic & Doug James Wilson, 2021. "A systematic review of charging infrastructure location problem for electric vehicles," Transport Reviews, Taylor & Francis Journals, vol. 41(4), pages 432-455, July.
    2. Guo, Fang & Yang, Jun & Lu, Jianyi, 2018. "The battery charging station location problem: Impact of users’ range anxiety and distance convenience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 1-18.
    3. Andrenacci, N. & Ragona, R. & Valenti, G., 2016. "A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas," Applied Energy, Elsevier, vol. 182(C), pages 39-46.
    4. Asamer, Johannes & Reinthaler, Martin & Ruthmair, Mario & Straub, Markus & Puchinger, Jakob, 2016. "Optimizing charging station locations for urban taxi providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 233-246.
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