Energy efficiency has become a major issue in trade, transportation and environment protection. While the next generation of zero emission propulsion systems still have difficulties in reaching similar travel distances as power-trains with combustion engines, it is already possible to increase fuel efficiency in regular vehicles by applying a more fuel efficient driving behavior. The rise of V2X technologies have opened up new possibilities for safety and energy efficiency applications. This publication proposes a model predictive approach that makes use of a power-train model and a sequence of traffic lights over a finite optimization horizon. The optimization problem is solved in a unified manner, i.e. power-train properties and traffic light phases are not considered separately but evaluated in a single cost function. A stagewise forward-backward Dynamic Programming approach involving cost reutilization is used for optimization. In order to further decrease the search space, certain continuous entities are not explicitly regarded as a state component, but rather calculated during optimization.


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    Titel :

    Unified predictive fuel efficiency optimization using traffic light sequence information


    Beteiligte:
    Guan, Tianyi (Autor:in) / Frey, Christian W. (Autor:in)

    Kongress:

    2016


    Erscheinungsdatum :

    2016


    Format / Umfang :

    6 pages



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    UNIFIED PREDICTIVE FUEL EFFICIENCY OPTIMIZATION USING TRAFFIC LIGHT SEQUENCE INFORMATION

    Guan, Tianyi / Frey, Christian Walter | British Library Conference Proceedings | 2016





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