This paper proposes to use Gaussian process regression to predict the consumption of a plug-in electric hybrid vehicle from low-quality data. We specify background knowledge regarding new operating points and information regarding the noise process. This makes it possible to adapt the original (naive’) model. Experiments realized using dynamic and energetic models simulated electrified vehicle show the interest of our approach in order to improve robustness against scarce and noisy data.


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    Title :

    Vehicle consumption estimation via calibrated Gaussian Process regression


    Contributors:


    Publication date :

    2022-06-05


    Size :

    2203536 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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