2026-06-09T08:48:22Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/69642024-05-20T07:52:10Zcom_10259.4_104com_10259_2604col_10259_6848

Luque Rodríguez, Pablo caf31a40-4ba8-4190-9dee-f8131ca0557e 600 Álvarez Mántaras, Daniel 46994fd8-0fb4-4e8f-b2d6-c293f48dd825 600 Roces García, Jorge 5352307f-77cc-4eac-be2a-152625e61d7f 600 Castejón Herrer, Luis 6cf50e3c-4be7-439c-b625-1f7d476c358d 600 Malón Litago, Hugo 0c5a1a65-9c94-4fde-a04c-aa5e12bd49d6 600 2022-09-21T07:25:41Z 2022-09-21T07:25:41Z 2021-07 978-84-18465-12-3 http://hdl.handle.net/10259/6964 10.36443/10259/6964 Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos The global challenge to reduce emissions of polluting gases and greenhouse gases has forced the development of alternatives to the traditional internal combustion engine vehicles, such as electric or hybrid vehicles. The electric powertrain are the most efficient for delivery trucks or urban buses, due to acceleration and deceleration patterns make them inefficient for using internal combustion engines. Despite this, its range and purchase cost are the main factors limiting the use of electric vehicles in these applications. Range and purchase cost of an electric vehicles are mainly related to the energy storage system. Therefore, the optimum size of the battery pack should be considered as the design goal of a vehicle when its application is known. This paper presents a methodology to optimize the battery pack of an electric vehicle according to a given route run in a target time. Therefore, it would be applicable to delivery vehicles, buses and any vehicle whose route and travel time are known in advance. The proposed methodology allows minimizing the energy consumption by determining the optimal powertrain ratio for a given track, setting the travel time as an objective. A full vehicle model and a multi-objective genetic algorithms are used for this matter. This work was supported by the University Institute of Industrial Technology of Asturias (IUTA). application/pdf eng Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional R-Evolucionando el transporte http://hdl.handle.net/10259/6490 https://doi.org/10.36443/9788418465123 Vehículos eléctricos Formas de movilidad Electric vehicles Means of mobility Ingeniería civil Transportes Civil engineering Transportation Optimization of the powertrain of electric vehicles for a given route info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/openAccess 2081 2092 THUMBNAIL Luque_CIT2021_2081-2092.pdf.jpg Luque_CIT2021_2081-2092.pdf.jpg IM Thumbnail image/jpeg 3918 https://riubu.ubu.es/bitstream/10259/6964/3/Luque_CIT2021_2081-2092.pdf.jpg 41f0cab8dd53d742caf3ffadea27eb0a MD5 3 LICENSE license.txt license.txt text/plain; charset=utf-8 1362 https://riubu.ubu.es/bitstream/10259/6964/2/license.txt 5d013bfa6e473ff0db22cd82a4d71a70 MD5 2 ORIGINAL Luque_CIT2021_2081-2092.pdf Luque_CIT2021_2081-2092.pdf application/pdf 517042 https://riubu.ubu.es/bitstream/10259/6964/1/Luque_CIT2021_2081-2092.pdf b23d8b8f678697314af19f7c0c9daeb3 MD5 1 10259/6964 oai:riubu.ubu.es:10259/6964 2024-05-20 09:52:10.238 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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