The efficiency gain of a hybrid drive can be further improved by optimizing the torque split. However, this requires additional input data for the simulation of a prediction. The most important information here is the preceding speed and altitude profile, as these can be used to predict the torque required to handle the driving task. A prediction module developed for this purpose accesses geo-data services (e.g. here-maps) and determines various route information for the route ahead. The information includes radius of curvature, gradient angle and speed limit. These are processed in the prediction module and used to determine the speed ahead. Based on this speed profile, the online optimizing operating strategy calculates the torque split of the hybrid powertrain for the prediction horizon so that lower fuel consumption is possible. Additional constraints such as a reduction in engine state changes, maximum torque gradients or a desired battery state of charge are taken into account. Through online optimization, the operating strategy also reacts to unpredictable variables such as unexpected route changes or deviations from the predicted speed profile.


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    Titel :

    Development of a Prediction Module for a Hybrid Operating Strategy Using Geo-Data


    Weitere Titelangaben:

    Proceedings


    Beteiligte:
    Bargende, Michael (Herausgeber:in) / Reuss, Hans-Christian (Herausgeber:in) / Wagner, Andreas (Herausgeber:in) / Riegelbeck, Christian (Autor:in) / Stalp, Alexander (Autor:in) / Schade, Daniel (Autor:in) / Beidl, Christian (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-03-14


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Deutsch




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