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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| Format: | Elektronisch Buchkapitel |
| Sprache: | Englisch |
| Veröffentlicht: |
Karlsruhe
KIT Scientific Publishing
2022
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| Schriftenreihe: | Karlsruher Schriftenreihe Fahrzeugsystemtechnik
6 |
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| Online-Zugang: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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