• DocumentCode
    725486
  • Title

    EVs mass adoption in Colombia — A first approach model

  • Author

    Hinestroza Olascuaga, Laura M. ; Rosero Garcia, Javier A. ; Puerto Pinzon, John E.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. del Norte, Barranquilla, Colombia
  • fYear
    2015
  • fDate
    10-13 June 2015
  • Firstpage
    1285
  • Lastpage
    1290
  • Abstract
    In Colombia, the electrification of the transportation sector has become an interesting possibility to consider in order to reduce pollution, global warming and promote efficient vehicles. Currently, most vehicles run on an internal combustion engine (ICE). However, the introduction of electric vehicles (EVs) raises questions regarding the impact of these alternative technologies on: users´ driving patterns, the mobility of cities, energy consumption, environmental impact, the energy distribution network, comfort conditions and adaptation to new ranges and speeds. Therefore, given their limitations, it is necessary to know the potential that the EVs technologies have in order to be properly adopted by users. This paper describes the application of a statistical prediction model, which determines the EVs technology that is most likely to be adopted in the city of Bogota, Colombia.
  • Keywords
    electric vehicles; internal combustion engines; power consumption; statistical analysis; Bogota city; Colombia; EV mass adoption; city mobility; comfort conditions; electric vehicles; energy consumption; energy distribution network; environmental impact; internal combustion engine; statistical prediction; users driving patterns; Analytical models; Cities and towns; Electric potential; Maintenance engineering; Mathematical model; Predictive models; Vehicles; electric vehicles; mass adoption; prediction model; statistics; user;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4799-7992-9
  • Type

    conf

  • DOI
    10.1109/EEEIC.2015.7165355
  • Filename
    7165355