Flottendatenbasierte physikalische Routenenergiebedarfsprognose

Abstract

To work towards climate goals with energetic planning functions in electric vehicles, a precise energy demand forecast along planned routes is essential, which separately quantifies relevant influences. For that this work shows a new driving profile prediction, which models energy flows while driving and recuperating on any link of a route with just 5 parameters. This work shows example applications of the model range forecasting and temporal route optimization.