An Efficient Hybrid Algorithm for Energy Expenditure Estimation for Electric Vehicles in Urban Service Enterprises

Mariusz Izdebski and Marianna Jacyna
Additional contact information
Mariusz Izdebski: Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland
Marianna Jacyna: Faculty of Transport, Warsaw University of Technology, 00-662 Warsaw, Poland

Energies, 2021, vol. 14, issue 7, 1-23

Abstract: The article deals with the decision problems of estimating the energy expenditure of low-emission fleets in urban service companies due to environmental safety. One of the most important problems of today’s transport policy of many city authorities is the ecological safety of its inhabitants. The basic measures are aimed at banning high-emission vehicles from city centers and promoting the introduction of zero-emission vehicles, such as electric or hybrid cars. The authors proposed an original approach to the decision model, in which the energy expenditure from the use of electric vehicles was defined as a criterion function. The boundary conditions took into account limitations typical of an electric vehicle, e.g., maximum range or battery charging time. To solve the problem, the authors proposed an efficient hybrid algorithm based on ant colony algorithm and genetic algorithm. The verification was made for the example of a utility company serving a medium-sized city in the eastern part of Poland.

Keywords: e-mobility; energy expenditure; electric vehicle; environmental impacts; hybrid algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/7/2004/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/7/2004/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:7:p:2004-:d:530458

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().