The emergence of new energy vehicles, especially electric vehicles (EV), has brought many development prospects. Power cuts in private electric cars can cause drivers to panic over long trips. Therefore, this paper proposes a charging path planning method for EV considering the influence of road condition information. This paper first analyzes the influence of energy consumption, vehicle delay estimation and traffic impedance under the control of different phase signals. On this basis, a path planning model is established to study the charging path planning of electric vehicles under the influence of road condition information. Finally, the feasibility of the model is verified by comparing different algorithms and different path selection results with and without traffic signal control, which provides a theoretical basis for the research of path intelligence guidance system.


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    Titel :

    Path Selection Optimization of Electric Vehicle Considering Traffic Condition Information


    Beteiligte:
    Zhao, Aolei (Autor:in) / Xu, Yongneng (Autor:in) / Liu, Wenya (Autor:in)

    Kongress:

    21st COTA International Conference of Transportation Professionals ; 2021 ; Xi’an, China


    Erschienen in:

    CICTP 2021 ; 1020-1030


    Erscheinungsdatum :

    14.12.2021




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch