This paper presents a method for increasing fuel economy using traffic data and a model predictive controller. Using knowledge of the traffic ahead, a vehicle can react to changes in traffic density or speed before they happen, increasing the efficiency of a trip and providing valuable information to the driver. In particular, the traffic information is used to determine a time-varying velocity envelope that the vehicle must satisfy. Then, a vehicle model is used to compute the vehicle speed profile that minimizes fuel use and satisfies the velocity constraints. Simulation results' show the feasibility of the proposed approach on a passenger vehicle with minor hardware modifications required for its implementation.


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    Title :

    Integrating traffic data and model predictive control to improve fuel economy


    Additional title:

    Integration von Verkehrsdaten und modellprädiktiver Regelung zur Verbesserung der Kraftstoffeinsparung


    Contributors:


    Publication date :

    2009


    Size :

    6 Seiten, 8 Bilder, 9 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English