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Transportation Research Part B Methodological
Article . 2018 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Charge scheduling for electric freight vehicles

Authors: Pelletier, Samuel; Jabali, Ola; Laporte, Gilbert;

Charge scheduling for electric freight vehicles

Abstract

Abstract We consider a fleet of electric freight vehicles (EFVs) that must deliver goods to a set of customers over the course of multiple days. In an urban environment, EFVs are typically charged at a central depot and rarely use public charging stations during delivery routes. Therefore, the charging schedule at the depot must be planned ahead of time so as to allow the vehicles to complete their routes at minimal cost. Vehicle fleet operators are subject to commercial electricity rate plans, which should be accounted for in order to provide an accurate estimation of the energy-related costs and restrictions. In addition, high vehicle utilization rates can accelerate battery aging, thereby requiring degradation mitigation considerations. We develop and solve a comprehensive mathematical model that incorporates a large variety of features associated with the use of EFVs. These include a realistic charging process, time-dependent energy costs, battery degradation, grid restrictions, and facility-related demand charges. Extensive numerical experiments are conducted in order to draw managerial insights regarding the impact of such features on the charging schedules of EFVs.

Countries
United Kingdom, Italy
Keywords

Battery degradation, Electric freight vehicles, Charge scheduling, /dk/atira/pure/subjectarea/asjc/3300/3313; name=Transportation, Battery degradation; Charge scheduling; City logistics; Electric freight vehicles; Green transportation; Civil and Structural Engineering; Transportation, /dk/atira/pure/subjectarea/asjc/2200/2205; name=Civil and Structural Engineering, City logistics, Green transportation, /dk/atira/pure/sustainabledevelopmentgoals/sustainable_cities_and_communities; name=SDG 11 - Sustainable Cities and Communities

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    120
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
120
Top 1%
Top 10%
Top 1%
Green