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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| Main Author: | |
|---|---|
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
Karlsruhe
KIT Scientific Publishing
2022
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| Series: | Karlsruher Schriftenreihe Fahrzeugsystemtechnik
6 |
| Subjects: | |
| Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 245 | 1 | 0 | |a Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models |
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| 520 | |a 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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| 653 | |a Elektromobilität | ||
| 653 | |a Vorhersagen | ||
| 653 | |a Algorithmen | ||
| 653 | |a Fahrzeugtechnik | ||
| 653 | |a Energiemanagement | ||
| 653 | |a E-Mobility | ||
| 653 | |a Forecasting | ||
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| 653 | |a Vehicle Technology | ||
| 653 | |a Energy Management | ||
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