A methodology originally developed to predict vehicle emissions was applied to prediction of fuel consumption for 56 over-the-road heavy-duty trucks recruited in southern California. The method employed measurements exercised over chassis dynamometer cycles and the properties of those cycles. Nine driving cycle properties and their combinations were used to predict fuel consumption over an “unseen” cycle, based on measurements from up to four different baseline driving cycles. The results showed that the use of average velocity and average positive acceleration was suitable for the translation of fuel consumption between cycles, producing the lowest prediction error among the cases considered.


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    Title :

    Heavy Duty Truck Fuel Consumption Prediction Based on Driving Cycle Properties


    Contributors:


    Publication date :

    2012-11-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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