The electrification of vehicles has the potential to significantly reduce greenhouse gas emissions and environmental impacts on transportation. However, locating charging infrastructure for electric vehicles has become increasingly complex. This research examines the distribution system of a logistics firm located in Gothenburg, Sweden, and the problem of allocating shared or semi-public charging stations for their fleet of vehicles. A real-time database was set up to record trip data for the company's fleet of freight vehicles, and data from over 110,000 trips were collected from November 2021 to May 2022. The study proposes parking locations during daytime as potential sites for shared charging stations, and the problem of allocating shared charging stations is formulated as a Location Set Covering Problem (LSCP). The goal is to provide decision-making support for logistics companies transitioning to electric vehicles. The model proposed in this study can be easily adapted to other freight transport systems, facilitating a swift transition to eco-friendly freight transportation.


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    Titel :

    Optimization of Freight Charging Infrastructure Placement Using Multiday Travel Data


    Beteiligte:
    Fu, Jiali (Autor:in) / Bhatti, Harrison John (Autor:in) / Eek, Magnus (Autor:in)


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    513668 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch