Non-Linear Model Predictive Control of Cabin Temperature and Air Quality in Fully Electric Vehicles

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dc.contributor.authorGlos, Jancs
dc.contributor.authorOtava, Lukášcs
dc.contributor.authorVáclavek, Pavelcs
dc.coverage.issue2cs
dc.coverage.volume70cs
dc.date.accessioned2021-04-19T06:57:23Z
dc.date.available2021-04-19T06:57:23Z
dc.date.issued2021-01-25cs
dc.description.abstractThis article describes an application of Non-linear Model Predictive Control algorithms on energy efficient control of fully electric vehicle cabin temperature and air quality. Since fully electric vehicles can not utilize waste heat from a powertrain (or there is not enough waste heat) as ICE vehicles do, it is necessary to employ advanced control approaches (especially for cabin heating) due to the possible mileage lost by using energy from the batteries for cabin conditioning. The basic idea behind this is to avoid the heat losses caused by excessive air exchange and to ensure a satisfactory air quality in combination with a user defined temperature. The Non-linear Model Predictive control algorithms were successfully implemented into an Infineon AURIX Tricore microcontroller and tested within a Processor in the Loop simulation.en
dc.formattextcs
dc.format.extent1216-1229cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. 2021, vol. 70, issue 2, p. 1216-1229.en
dc.identifier.doi10.1109/TVT.2021.3054170cs
dc.identifier.issn0018-9545cs
dc.identifier.other168057cs
dc.identifier.urihttp://hdl.handle.net/11012/196512
dc.language.isoencs
dc.publisherIEEEcs
dc.relation"European Union (EU)" & "Horizon 2020"en
dc.relation"Euratom" & "Euratom research & training programme 2014-2018"en
dc.relation.ispartofIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGYcs
dc.relation.projectIdinfo:eu-repo/grantAgreement/EC/H2020/653514/EU//OSEM-EVen
dc.relation.projectIdinfo:eu-repo/grantAgreement/EC/H2020/857306/EU//RICAIPen
dc.relation.urihttps://ieeexplore.ieee.org/document/9335535cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/0018-9545/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectHeating systemsen
dc.subjectResistance heatingen
dc.subjectWaste heaten
dc.subjectAtmospheric modelingen
dc.subjectAir qualityen
dc.subjectHeat pumpsen
dc.subjectTemperature controlen
dc.subjectAir quality controlen
dc.subjectbattery electric vehicleen
dc.subjectextended kalman filteren
dc.subjectfully electric vehicleen
dc.subjectnon-linear model predictive controlen
dc.subjecttemperature controlen
dc.subjectvehicle cabin modelen
dc.titleNon-Linear Model Predictive Control of Cabin Temperature and Air Quality in Fully Electric Vehiclesen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-168057en
sync.item.dbtypeVAVen
sync.item.insts2021.05.17 04:53:33en
sync.item.modts2021.05.17 04:15:13en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav automatizace a měřicí technikycs
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika pro materiálové vědycs
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