dc.contributor.author | Alonso del Valle, Jorge | |
dc.contributor.author | Viera Pérez, Juan Carlos | |
dc.contributor.author | Anseán González, David | |
dc.contributor.author | Brañas Reyes, Christian | |
dc.contributor.author | Luque Rodríguez, Pablo | |
dc.contributor.author | Álvarez Mántaras, Daniel | |
dc.contributor.author | Fernández Pulido, Yoana | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2019-09-06T12:21:05Z | |
dc.date.available | 2019-09-06T12:21:05Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2352-1465 | |
dc.identifier.issn | 2352-1457 | |
dc.identifier.other | TEC2016-80700-R | es_ES |
dc.identifier.uri | http://hdl.handle.net/10902/16852 | |
dc.description.abstract | This work develops a software tool to calculate and predict the energy consumption of an electric vehicle (EV) for any desired route. The software tool is based on a mathematical model of an electric vehicle, which relates the energy consumption of the vehicle with factors such as the speed and the terrain slope. In addition, factors such as driving style, weather conditions and traffic congestion can be taken into account. The model has been validated with real data from an electric vehicle. On the other hand, this work proposes a methodology to use this tool with any other EV, as long as its basic characteristics are known.
The results obtained in this work are applied in automated testing systems, specific for EV storage systems at laboratory level. The main advantage lies in the use of more realistic power profiles than those commonly used and proposed in the specialized literature (eg, FUDS). In addition, the proposed methodology can be applied to any EV, in different scenarios of orography, traffic, climatology, etc. | es_ES |
dc.description.sponsorship | This work was supported by the Science of Innovation Spanish Ministry and FEDER funds under the Project TEC2016-80700-R (AEI/FEDER, UE), by the Principality of Asturias Government under project FC-15GRUPIN14-073 and the University Institute of Industrial Technology of Asturias (IUTA) under project SV-15GIJON-1.13. | es_ES |
dc.format.extent | 8 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Transportation Research Procedia, 2018, 33, 35-42 | es_ES |
dc.source | 13th Conference on Transport Engineering (CIT2018), Gijón, 35-42 | es_ES |
dc.subject.other | Electric vehicles | es_ES |
dc.subject.other | Batteries | es_ES |
dc.subject.other | Energy consumption | es_ES |
dc.subject.other | Energy efficiency | es_ES |
dc.subject.other | Energy management | es_ES |
dc.title | Design and validation of a tool for prognosis of the energy consumption and performance in electric vehicles | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.identifier.DOI | 10.1016/j.trpro.2018.10.073 | |
dc.type.version | publishedVersion | es_ES |