Geo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EV

Simple item page
dc.contributor.authorPrieto, P.
dc.contributor.authorTrancho, E.
dc.contributor.authorArteta, B.
dc.contributor.authorParra, A.
dc.contributor.authorCoupeau, A.
dc.contributor.authorCagigas, D.
dc.contributor.authorIbarra, E.
dc.contributor.institutionPOWERTRAIN
dc.contributor.institutionTecnalia Research & Innovation
dc.date.issued2019-10
dc.descriptionPublisher Copyright: © 2019 IEEE.
dc.description.abstractNowadays, the shortage of energy and environmental pollution are considered as relevant problems due to the high amount of traditional automotive vehicles with internal combustion engines (ICEs). Electric vehicle (EV) is one of the solutions to localize the energy source and the best choice for saving energy and provide zero emission vehicles. However, their main drawback when compared to conventional vehicles is their limited energy storage capacity, resulting in poor driving ranges. In order to mitigate this issue, the scientific community is extensively researching on energy optimization and prediction strategies to extend the autonomy of EV. In general, such strategies require the knowledge of the route profile, being of capital importance to identify whether the vehicle is on route or not. Considering this, in this paper, a route tracking diagnosis strategy is proposed and tested. The proposed strategy relies on the information provided by the Google Maps API (Application Programming Interface) to calculate the vehicles reference route. Additionally, a Global Positioning System (GPS) device is used to monitor the real vehicle position. The proposed strategy is validated throughout simulation, Driver in the Loop (DiL) test and experimental tests.en
dc.description.statusPeer reviewed
dc.format.extent7
dc.format.extent3684103
dc.identifier.citationPrieto , P , Trancho , E , Arteta , B , Parra , A , Coupeau , A , Cagigas , D & Ibarra , E 2019 , Geo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EV . in unknown : IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society . 2019-October , IEEE , pp. 2694-2700 , 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 , Lisbon , Portugal , 14/10/19 . https://doi.org/10.1109/IECON.2019.8927769
dc.identifier.citationconference
dc.identifier.doi10.1109/IECON.2019.8927769
dc.identifier.isbn978-1-7281-4879-3
dc.identifier.isbn978-1-7281-4878-6
dc.identifier.isbn9781728148786
dc.identifier.otherresearchoutputwizard: 11556/1270
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85084051053&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofunknown
dc.relation.ispartofseries2019-October
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordsBEV
dc.subject.keywordsPHEV
dc.subject.keywordsEnergy consumption estimation
dc.subject.keywordsOptimization
dc.subject.keywordsTracking diagnosis
dc.subject.keywordsBEV
dc.subject.keywordsPHEV
dc.subject.keywordsEnergy consumption estimation
dc.subject.keywordsOptimization
dc.subject.keywordsTracking diagnosis
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsElectrical and Electronic Engineering
dc.subject.keywordsSDG 7 - Affordable and Clean Energy
dc.subject.keywordsSDG 13 - Climate Action
dc.subject.keywordsProject ID
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769944/EU/Smart-Taylored L-category Electric Vehicle demonstration in hEtherogeneous urbanuse-cases/STEVE
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/824311/EU/Advanced Architectures Chassis/Traction concept for Future Electric vehicles/ACHILES
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769902/EU/Design OptiMisation for efficient electric vehicles based on a USer-centric approach/DOMUS
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769944/EU/Smart-Taylored L-category Electric Vehicle demonstration in hEtherogeneous urbanuse-cases/STEVE
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/824311/EU/Advanced Architectures Chassis/Traction concept for Future Electric vehicles/ACHILES
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769902/EU/Design OptiMisation for efficient electric vehicles based on a USer-centric approach/DOMUS
dc.subject.keywordsFunding Info
dc.subject.keywordsThis work was supported in part by the H2020 European Commission under Grant 769944 (STEVE Project), Grant 824311 (ACHILES Project) and Grant 769902 (DOMUS Project) and in part by the research projects GANICS (KK-2017/00050), SICSOL (KK-2018/00064) and ENSOL (KK-2018/00040), within the ELKARTEK program of the Government of the Basque Country. Finally, this work has been supported by the Department of Education, Linguistic Policy and Culture of the Basque Government within the fund for research groups of the Basque university system IT978-16.
dc.subject.keywordsThis work was supported in part by the H2020 European Commission under Grant 769944 (STEVE Project), Grant 824311 (ACHILES Project) and Grant 769902 (DOMUS Project) and in part by the research projects GANICS (KK-2017/00050), SICSOL (KK-2018/00064) and ENSOL (KK-2018/00040), within the ELKARTEK program of the Government of the Basque Country. Finally, this work has been supported by the Department of Education, Linguistic Policy and Culture of the Basque Government within the fund for research groups of the Basque university system IT978-16.
dc.titleGeo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EVen
dc.typeconference output
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2019_IECON_Geofence__.pdf
Size:
3.51 MB
Format:
Adobe Portable Document Format
Download