Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models

This work aims at improving the energy consumption forecast of electric vehicles by enhancing the prediction with a notion of uncertainty. The algorithm itself learns from driver and traffic data in a training set to generate accurate, driver-individual energy consumption forecasts.

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Bibliographic Details
Main Author: Scheubner, Stefan (auth)
Format: Electronic Book Chapter
Language:English
Published: Karlsruhe KIT Scientific Publishing 2022
Series:Karlsruher Schriftenreihe Fahrzeugsystemtechnik
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