Smart charging strategies for heavy electric vehicles

With emission standards tightening around the world and the popularity of electric cars rising, the electrification of heavy-duty vehicles (e.g., diesel trucks) appears to be a natural progression. For electric truck (ET) charging, a return-to-base strategy with chargers located where trucks begin and end each day, such as trucks used in cargo, freight, and delivery entities, is becoming increasingly viable and attractive. This return-to-base strategy; however, has impacts on the peak demand of a facility which can contribute to an increase in demand charge and requires electrical asset upgrades in certain circumstances. This challenge is different and unique compared to the light-duty passenger vehicles charging challenge (i.e., low distributed charging load and longer charging periods). To address this ET charging challenge, this paper proposes a smart charging system (SCS) that manages the charging process of ETs at their commercial facilities, with the objective of minimizing the peak demand of the aggregate load profile at the facility.The authors' simulation studies show the effectiveness of the proposed SCS in reducing the peak demand of the facility. The proposed solution can achieve a monthly saving in demand charge of up to 54% compared to uncontrolled charging schemes.

• Record URL:
  https://doi.org/10.1016/j.etran.2022.100182
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2590116822000285
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/25901168
• Supplemental Notes:
  • © 2022 Elsevier B.V. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Al-Hanahi, Bassam
  • 0000-0002-5205-1059
  • Ahmad, Iftekhar
  • Habibi, Daryoush
  • Masoum, Mohammad A S
• Publication Date: 2022-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 100182
• Serial:
  • eTransportation
  • Volume: 13
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2590-1168
  • Serial URL: https://www.sciencedirect.com/journal/etransportation

Subject/Index Terms

• TRT Terms: Electric vehicle charging; Electric vehicles; Intelligent control systems; Trucks
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01849183
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 23 2022 9:16AM