The study of charging choice for electric vehicle holds significant importance for the promotion of new energy vehicles, the realization of energy saving and emission reduction. Based on one month's global positioning system data of electric vehicles, this study segments the daily usage behaviors of electric vehicles. It identifies the starting and ending points of trips and extracts the instantaneous state information of vehicles at trip endpoints. This information is used as independent variables for electric vehicle charging choice, with the presence of charging at trip endpoints as the dependent variable. A binary Logit model is employed to establish a model analyzing the charging choice behavior at the endpoints of electric vehicle trips. The model's parameters are then estimated and tested. The results indicate that the state of charge, cumulative mileage, and time significantly impact the charging choice of electric vehicle at trip endpoints.


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    Titel :

    Study on Charging Choice of Electric Vehicle Based on GPS Data


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Meng, Lingyun (Herausgeber:in) / Qian, Yongsheng (Herausgeber:in) / Bai, Yun (Herausgeber:in) / Lv, Bin (Herausgeber:in) / Tang, Yuanjie (Herausgeber:in) / Jingchun, Jia (Autor:in) / Hao, Yue (Autor:in) / Di, Cui (Autor:in)

    Kongress:

    International Conference on Traffic and Transportation Studies ; 2024 ; Lanzhou, China August 23, 2024 - August 25, 2024



    Erscheinungsdatum :

    21.11.2024


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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