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Flottendatenbasierte physikalische Routenenergiebedarfsprognose

Flottendatenbasierte physikalische Routenenergiebedarfsprognose

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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.

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DOI: 10.5445/KSP/1000168810

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