Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Use of neural networks for estimating EVs battery SOC considering driving style
Year:2015
Research Areas
  • Mechanical engineering,
  • Information technology and adata processing,
  • Electric engineers, electronic and automatic (eil)
Information
Abstract
One of the great problems of electric vehicles is the limited autonomy, which causes stress on drivers of insecurity to reach the destination. Vehicles implement algorithms for the estimation of autonomy depending on driving style from the previous sections. However, it is easy to see that this estimation of power consumption is not always reliable and does not take into account relevant factors of influence. This paper presents a consumption estimation based on the knowledge of how the way of driving and the route. To this end, a neural network have been developed which takes as input data information from the CAN bus, data from specific instrumentation and vehicle positioning, and provides as output variable the state of charge consumption. Tests have been performed with 8 drivers along 2 routes of different characteristics in Madrid (Spain) and results have been highly successful.
International
Si
Congress
22nd World Congress and Exhibition on Intelligent Transport Systems and Services.
960
Place
Bordeaux
Reviewers
Si
ISBN/ISSN
0000-0000
Start Date
05/10/2015
End Date
09/10/2015
From page
1
To page
8
ITS WORLD CONGRESS 2015 proceedings
Participants
  • Autor: Felipe Jimenez Alonso (UPM)
  • Autor: Francisco Serradilla Garcia (UPM)
  • Autor: Jose Eugenio Naranjo Hernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inv. en Seguridad e Impacto Medioambiental de Vehículos y Transportes (GIVET)
  • Centro o Instituto I+D+i: Instituto Universitario de Investigación del Automóvil (INSIA)
  • Departamento: Inteligencia Artificial
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