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Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models

dc.contributor.authorScheubner, Stefan
dc.date.accessioned2025-03-07T21:11:36Z
dc.date.available2025-03-07T21:11:36Z
dc.date.issued2022
dc.date.submitted2022-06-20T19:09:54Z
dc.identifierONIX_20220620_9783731511663_74
dc.identifierOCN: 1348375824
dc.identifier1869-6058
dc.identifierhttps://library.oapen.org/handle/20.500.12657/56964
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/167000
dc.description.abstractThis 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.
dc.languageEnglish
dc.relation.ispartofseriesKarlsruher Schriftenreihe Fahrzeugsystemtechnik
dc.rightsopen access
dc.subject.otherElektromobilität
dc.subject.otherVorhersagen
dc.subject.otherAlgorithmen
dc.subject.otherFahrzeugtechnik
dc.subject.otherEnergiemanagement
dc.subject.otherE-Mobility
dc.subject.otherForecasting
dc.subject.otherAlgorithms
dc.subject.otherVehicle Technology
dc.subject.otherEnergy Management
dc.titleStochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models
dc.typebook
oapen.identifier.doi10.5445/KSP/1000143200
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.relation.isbn9783731511663
oapen.collectionAG Universitätsverlage
oapen.imprintKIT Scientific Publishing
oapen.pages192
oapen.place.publicationKarlsruhe
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
dc.seriesnumber6
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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open access
Except where otherwise noted, this item's license is described as open access