Latest revision as of 21:14, 3 February 2021

Abstract

ng the potential of electric vehicles against actual user needs is a key-issue to integrate individual e-mobility in sustainable transport. An extensive analysis of real-life mobility has been carried out, in view of deriving and quantifying the potential of introducing electric vehicles in urban environment. A large activity data set collected with GPS black boxes mounted on approximately 16,000 vehicles monitored for a one-month period in the Italian province and city of Modena has been purchased and post-processed in order to characterise vehicles’ driving patterns. The ability of different types of electric vehicles to cover the real mobility needs of the users has been then investigated, estimating the percentage of individual trips which might be suitable to be performed by electric vehicles, as well as their potential impact on the electric energy distribution grid depending on different recharging behavioural models. The results show that more than 80% of these trips might be driven electric and that a fleet share lying between 10% and 25% can be immediately converted to battery electric vehicles, being not affected by their limited range. The quantitative key-insights based on real-life mobility data enable to address several issues, ranging from technological aspects, policy impacts and interoperability possibilities offered by the integration of electromobility with the energy distribution grid

Document type: Article

Full document

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.3390/wevj6010100 under the license https://creativecommons.org/licenses/by

• http://www.mdpi.com/2032-6653/6/1/100/pdf under the license http://creativecommons.org/licenses/by/3.0/

• https://www.mdpi.com/2032-6653/6/1/100/pdf under the license cc-by

• http://www.mdpi.com/2032-6653/6/1/100/pdf,

http://dx.doi.org/10.3390/wevj6010100 under the license cc-by

• http://xplorestaging.ieee.org/ielx7/6902670/6914705/06914764.pdf?arnumber=6914764,

http://dx.doi.org/10.1109/evs.2013.6914764 under the license https://creativecommons.org/licenses/by/4.0/

• https://ieeexplore.ieee.org/document/6914764,

https://www.mdpi.com/2032-6653/6/1/100,

https://www.mdpi.com/2032-6653/6/1/100/pdf,

http://publications.jrc.ec.europa.eu/repository/handle/JRC82171,

https://academic.microsoft.com/#/detail/2219184114

DOIS: 10.3390/wevj6010100 10.1109/evs.2013.6914764