Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/19439

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dc.contributor.authorFerreira, João C.-
dc.contributor.authorMonteiro, Vítor Duarte Fernandes-
dc.contributor.authorAfonso, João L.-
dc.date.accessioned2012-05-22T14:21:40Z-
dc.date.available2012-05-22T14:21:40Z-
dc.date.issued2012-03-
dc.identifier.urihttps://hdl.handle.net/1822/19439-
dc.description.abstractOur work proposal is based on the past driving data that are stored in a driver profile, and using real time information about the Electric Vehicle parameters (e.g. speed and energy stored in the batteries), combined with external parameters (e.g. condi-tions of roads, traffic, and weather), determine the range autonomy accurately, taking into account the historical driver behavior. The driver profile is based on the stored data, which acts as training set for a Data Mining approach, in order to estimate the Electric Vehicle range. The Data Mining approach uses a regression model aiming to find the better range autonomy, which is used to represent the current Electric Vehicle range autonomy on a map.por
dc.description.sponsorshipFundação para a Ciência e a Tecnologia (FCT)por
dc.language.isoengpor
dc.rightsopenAccesspor
dc.subjectRange predictionpor
dc.subjectData miningpor
dc.subjectDriver profilepor
dc.subjectRange anxiety problempor
dc.subjectElectric vehiclepor
dc.titleData mining approach for range prediction of electric vehiclepor
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.publicationstatuspublishedpor
oaire.citationStartPage1por
oaire.citationEndPage15por
oaire.citationConferencePlaceMunich, Germanypor
oaire.citationTitleConference on Future Automotive Technology - Focus Electromobilitypor
sdum.conferencePublicationConference on Future Automotive Technology - Focus Electromobilitypor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings
DEI - Artigos em atas de congressos internacionais

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