9783731511663.pdf

9783731511663.pdf

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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Γλώσσα:English
Έκδοση: KIT Scientific Publishing 2022
Διαθέσιμο Online:https://www.ksp.kit.edu/site/books/m/10.5445/KSP/1000143200/
id oapen-20.500.12657-56964
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spelling oapen-20.500.12657-569642022-06-21T03:04:01Z Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models Scheubner, Stefan Elektromobilität Vorhersagen Algorithmen Fahrzeugtechnik Energiemanagement E-Mobility Forecasting Algorithms Vehicle Technology Energy Management bic Book Industry Communication::T Technology, engineering, agriculture::TG Mechanical engineering & materials 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. 2022-06-20T19:09:54Z 2022-06-20T19:09:54Z 2022 book ONIX_20220620_9783731511663_74 1869-6058 9783731511663 https://library.oapen.org/handle/20.500.12657/56964 eng Karlsruher Schriftenreihe Fahrzeugsystemtechnik application/pdf n/a 9783731511663.pdf https://www.ksp.kit.edu/site/books/m/10.5445/KSP/1000143200/ KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000143200 10.5445/KSP/1000143200 44e29711-8d53-496b-85cc-3d10c9469be9 9783731511663 KIT Scientific Publishing 6 192 Karlsruhe open access
institution OAPEN
collection DSpace
language English
description 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.
title 9783731511663.pdf
spellingShingle 9783731511663.pdf
title_short 9783731511663.pdf
title_full 9783731511663.pdf
title_fullStr 9783731511663.pdf
title_full_unstemmed 9783731511663.pdf
title_sort 9783731511663.pdf
publisher KIT Scientific Publishing
publishDate 2022
url https://www.ksp.kit.edu/site/books/m/10.5445/KSP/1000143200/
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