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
Link To Document :
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