Optimal energy management of hybrid electric vehicles requires a priori information regarding future driving conditions; the acquisition and processing of this information is nevertheless often neglected in academic research. This paper introduces a commuter route optimized energy management system, where the bulk of the computations are performed on a server. The idea is to identify commuter routes from historical driving data, using hierarchical agglomerative clustering, and then precompute an optimal solution to the energy management control problem with dynamic programming; the obtained solution can then be transmitted to the vehicle in the form of a lookup table. To investigate the potential of such a system, a simulation study is performed using a detailed vehicle model implemented in the Autonomie simulation environment for MATLAB/Simulink. The simulation results for a plug-in hybrid electric vehicle indicate that the average fuel consumption along the commuter route(s) can be reduced by 4%–9% and battery usage by 10%–15%.


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    Titel :

    Commuter Route Optimized Energy Management of Hybrid Electric Vehicles


    Beteiligte:
    Larsson, Viktor (Autor:in) / Johannesson Mardh, Lars (Autor:in) / Egardt, Bo (Autor:in) / Karlsson, Sten (Autor:in)


    Erscheinungsdatum :

    2014-06-01


    Format / Umfang :

    1802975 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch