This work aims at improving the energy consumption forecast of electric vehicles by enhancing the prediction with a notion of uncertainty. The algorithm itself learns from driver and traffic data in a training set to generate accurate, driver-individual energy consumption forecasts


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    Title :

    Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models


    Contributors:


    Publication date :

    2022


    Size :

    1 Online-Ressource (192 p.)



    Type of media :

    Book


    Type of material :

    Electronic Resource


    Language :

    Unknown