A methodology to estimate the energy consumption of an electric vehicle is presented. An approach to create a driving cycle based on data extracted from road planning software is developped; it is used to forecast the total cycle energy consumption. Results are compared to the ones obtained from the corresponding actual driving cycle. The influence of road elevation is taken into. Results match with regard to vehicle velocities, power demand and estimated energy consumption, with a maximum error of 10%. It can thus be concluded that road planning-based energy consumption estimation can be a useful tool by providing accurate information to drivers.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Autonomy estimation for EV based on road planning software


    Beteiligte:
    Chrenko, Daniela (Autor:in) / Ravey, Alexandre (Autor:in) / Roche, Robin (Autor:in) / Bouquain, David (Autor:in)


    Erscheinungsdatum :

    01.06.2014


    Format / Umfang :

    360977 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Electric Vehicle Autonomy: Realtime Dynamic Route Planning and Range Estimation Software

    Bailey, Carter / Jones, Bridger / Clark, Max et al. | IEEE | 2022


    Autonomy driving method and system based on road learning

    LEE MIN CHAE | Europäisches Patentamt | 2017

    Freier Zugriff

    Autonomy driving method and system based on road learning

    Europäisches Patentamt | 2023

    Freier Zugriff

    Autonomy in Spacecraft Software Architecture

    Hexmoor, H. / Florida AI Research Society | British Library Conference Proceedings | 1999


    ASAP: Autonomy through on-board planning

    Wojtkowiak, Harald / Balagurin, Oleskii / Fellinger, Gerhard et al. | IEEE | 2013