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.
Vehicle consumption estimation via calibrated Gaussian Process regression
2022-06-05
2203536 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
VEHICLE TRAJECTORY PREDICTION WITH GAUSSIAN PROCESS REGRESSION IN CONNECTED VEHICLE ENVIRONMENT
British Library Conference Proceedings | 2018
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