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.

Bibliographic Details
Format: eBook
Language:English
Published: Karlsruhe KIT Scientific Publishing 2022
Series:Karlsruher Schriftenreihe Fahrzeugsystemtechnik
Subjects:
Online Access:Open Access: DOAB: description of the publication
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