Abstract Electric vehicles for urban shared mobility services are important customers at public charging stations, and understanding their charging behavior is essential to the charging infrastructure planning and charging demand management. This study investigates the influencing factors on drivers’ charging station selections for a large-scale and fully electrified taxi fleet with nearly 20,000 unique vehicles and over 35,000 drivers. Drivers’ preference for a charging station is approximated by the driving time to it, and quantile regression models are estimated with explanatory variables on personal, charging station configuration, and built-environment factors. Study results suggest that whether a driver serves single- or double-shift, his or her charging habit, the charging station’s accessibility to subway stations, and the charging duration are important factors affecting the choice outcomes. Insights derived in this study have important implications for planning charging infrastructure and managing charging demand for city-wide electric vehicles.

    Highlights Analyzes charging station preference using data from fully-electrified taxi fleet. Quantifies heterogeneous impacts of influencing factors on charging preference. Identifies habit, station accessibility, and charging duration as main factors. Investigates single- and double-shift drivers’ charging preference differences. Provides insights to charging infrastructure planning and charging demand management.


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    Titel :

    Modeling the preference of electric shared mobility drivers in choosing charging stations


    Beteiligte:
    Guo, Yuntao (Autor:in) / Qian, Xinwu (Autor:in) / Lei, Tian (Autor:in) / Guo, Shuocheng (Autor:in) / Gong, Lei (Autor:in)


    Erscheinungsdatum :

    2022-07-14




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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