Fuel consumption analysis tool based on hybrid electric vehicle models

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dc.contributor.authorOtaola, Eneko
dc.contributor.authorArteta, Beñat
dc.contributor.authorPérez, Joshué
dc.contributor.authorSierra-Gonzalez, Andres
dc.contributor.authorPrieto, Pablo
dc.contributor.institutionPOWERTRAIN
dc.contributor.institutionCCAM
dc.date.accessioned2024-07-24T11:57:47Z
dc.date.available2024-07-24T11:57:47Z
dc.date.issued2023
dc.descriptionPublisher Copyright: © 2023 IEEE.
dc.description.abstractThe reduction of fuel consumption and Greenhouse Gases is of key importance during the last decades. Heavy-duty vehicles have been extensively researched due to the significant pollution produced. This work presents a novel simulation platform for different heavy-duty powertrain topologies: mainly combustion and parallel hybrid. This work was developed in the framework of a LONGRUN project, where a platform was implemented based on forward-looking formulation. This allows the assessment of hybrid control systems development, analysing the impact of the hybrid and electric topologies. We compared the results with a commercial tool (VECTO) adopted by the European Commission to validate the platform components over combustion powertrain analysis. In this paper, we provide a modular platform for heavy-duty vehicles, in a widely used software inside the automotive industry. Moreover, our tool has the possibility to implement hybrid electric vehicles powertrain topologies for the assessment of their control strategies and the analysis of fuel consumption and Greenhouse Gases emissions. The results show proposing results in terms of performance of the model used and fuel saving.en
dc.description.sponsorshipThe present work is supported by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 874972 and the ERABILH2 project, funded by the Basque Government’s Elkartek Research and Innovation program, under grant agreement KK-2021/00086.
dc.description.statusPeer reviewed
dc.identifier.citationOtaola , E , Arteta , B , Pérez , J , Sierra-Gonzalez , A & Prieto , P 2023 , Fuel consumption analysis tool based on hybrid electric vehicle models . in 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 . 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 , Institute of Electrical and Electronics Engineers Inc. , 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 , Detroit , United States , 21/06/23 . https://doi.org/10.1109/ITEC55900.2023.10187119
dc.identifier.citationconference
dc.identifier.doi10.1109/ITEC55900.2023.10187119
dc.identifier.isbn9798350397420
dc.identifier.urihttps://hdl.handle.net/11556/2769
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85168240558&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023
dc.relation.ispartofseries2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023
dc.relation.projectIDHorizon 2020 Framework Programme, H2020, 874972
dc.relation.projectIDEusko Jaurlaritza, KK-2021/00086
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordshybrid control strategies
dc.subject.keywordshybrid electric vehicle system architectures
dc.subject.keywordsvehicle simulation platform
dc.subject.keywordsEnergy Engineering and Power Technology
dc.subject.keywordsAutomotive Engineering
dc.subject.keywordsTransportation
dc.subject.keywordsControl and Optimization
dc.subject.keywordsSDG 7 - Affordable and Clean Energy
dc.subject.keywordsSDG 9 - Industry, Innovation, and Infrastructure
dc.subject.keywordsSDG 13 - Climate Action
dc.titleFuel consumption analysis tool based on hybrid electric vehicle modelsen
dc.typeconference output
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