2026-06-07T07:49:42Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/146412026-02-03T11:57:03Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Gago-Calderón, Alfonso
author
Maldonado Criado, Rubén
author
Fernández-Ramos, José
2017-10-16T11:19:32Z
2017-10-16T11:19:32Z
2017
EVS30
http://hdl.handle.net/10630/14641
http://orcid.org/0000-0002-2862-7329
Improving efficiency is one of the most important objectives of the Smart Cities standards, and Electric Vehicles (EVs). TICS can help to soften one of their main limitations –autonomy– planning efficient driving strategies. This paper evaluates the physical variables that have an impact on the EV consumption and presents an electronic architecture to monitor them in an Experimental Ultralight Electric Vehicle. This system includes a set of very low cost sensors integrated with a data logger and a GPRS transmission system that can connect, in real time, with a control center where a route-finding reinforcement-learning algorithm that helps to find the most-effective route and reduce the time spent on urban environment tips.
eng
by-nc-nd
Sistemas de información geográfica
Tráfico
Smart-Cities urban mobility management architecture for electric vehicles
conference output
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URL
https://riuma.uma.es/bitstreams/cebcaa32-9b17-40e4-936e-e7c0ef21d9cf/download
File
MD5
bf022e325883aafec8b7cfd97bc8ab3e
2858471
application/pdf
EVS30-1960823.pdf