Drivers of battery electric vehicles (BEVs) require an accurate and reliable energy consumption prediction along a chosen route to reduce range anxiety. The energy consumption for a future trip depends on a number of factors such as driving behavior, road topography information, weather conditions and traffic situation. This paper discusses an algorithm to predict the energy consumption for a future trip considering these influencing factors. The route information is obtained from OpenStreetMap and Shuttle Radar Topography Mission. The algorithm consists of an offline algorithm and an online algorithm. The offline algorithm is designed to provide information for the driver to make future driving plans, which provides a nominal energy consumption value and an energy consumption range before a trip begins. The online algorithm is designed to adjust the energy consumption prediction result based on current driving, which includes a vehicle parameter estimation algorithm and a driving behavior correction algorithm. The energy consumption prediction algorithm is verified by 30 driving tests, including city, rural, highway and hilly driving. A comparison shows that the measured energy consumption of all trips is within the energy consumption range provided by the offline algorithm and most of the differences between the measurement and nominal prediction are smaller than 10%. The offline prediction is used as a starting point and is corrected by the online algorithm during driving. The mean absolute percentage error between the measured energy consumption value and online prediction result of all trips is within 5%.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Battery electric vehicle energy consumption prediction for a trip based on route information


    Beteiligte:
    Wang, Jiquan (Autor:in) / Besselink, Igo (Autor:in) / Nijmeijer, Henk (Autor:in)


    Erscheinungsdatum :

    2018-09-01


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Route Prediction from Trip Observations

    Krumm, John / Froehlich, Jon | SAE Technical Papers | 2008


    Trip energy consumption estimation for electric buses

    Jinhua Ji / Yiming Bie / Ziling Zeng et al. | DOAJ | 2022

    Freier Zugriff

    Route prediction from trip observations

    Froehlich,J. / Krumm,J. / Univ.of Washington,US et al. | Kraftfahrwesen | 2008


    Route Prediction from Trip Observations

    Froehlich, J. / Krumm, J. / Society of Automotive Engineers | British Library Conference Proceedings | 2008


    ELECTRIC VEHICLE TRIP ENERGY PREDICTION BASED ON BASELINE AND DYNAMIC DRIVER MODELS

    WANG YUE-YUN / LI DONGXU / MAZZARA BRANDON D et al. | Europäisches Patentamt | 2023

    Freier Zugriff