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Placement of Fast-Charging Infrastructure for Long-Haul Road Freight Based on Spatio-Temporal Evaluation of En-Route Energy Needs

Ingelstrom, Mattias LU ; Arabani, Hamoun Pourroshanfekr LU ; Alakula, Mats LU orcid and Marquez-Fernandez, Francisco J. LU orcid (2025) In IEEE Transactions on Transportation Electrification
Abstract

The rapid progression of the electrification of road transport in many countries urges the need to make informed decisions on the location and size of the required charging infrastructure. This paper’s main contribution is a novel method to position fast-charging stations based on the transportation energy demand and to evaluate the performance of such charging infrastructure. Depending on their range and the availability of charging infrastructure, electric vehicles may need to adjust their route patterns to include en-route charging. Understanding and planning for these adjustments can help assess future charging infrastructure needs more effectively. The proposed method introduces a detailed agent-based simulation procedure to track... (More)

The rapid progression of the electrification of road transport in many countries urges the need to make informed decisions on the location and size of the required charging infrastructure. This paper’s main contribution is a novel method to position fast-charging stations based on the transportation energy demand and to evaluate the performance of such charging infrastructure. Depending on their range and the availability of charging infrastructure, electric vehicles may need to adjust their route patterns to include en-route charging. Understanding and planning for these adjustments can help assess future charging infrastructure needs more effectively. The proposed method introduces a detailed agent-based simulation procedure to track individual trucks assumed to be fully electric. The procedure allows for analyzing each vehicle’s and charging station’s specific power flows. A case study based on a one-to-one representation of Swedish long-haul road freight transport is created based on real-world data. The results demonstrate that using the presented method, 90% of the Swedish long-haul truck fleet can be electrified with 26 carefully placed charging stations. These stations vary in size between 10-60 MW, presenting a utilization of 30-53%. The paper also provides detailed time variations in charging needs, using the best available data.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
Agent-based modeling, Battery electric trucks, Charging infrastructure, Road transport-power grid interaction, Transport decarbonization, Zero-emission road freight transport
in
IEEE Transactions on Transportation Electrification
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:105016531298
ISSN
2332-7782
DOI
10.1109/TTE.2025.3610257
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2015 IEEE.
id
ea3fbc7e-38ce-48b8-b178-1048c73e830b
date added to LUP
2025-10-05 09:57:18
date last changed
2025-10-09 11:14:17
@article{ea3fbc7e-38ce-48b8-b178-1048c73e830b,
  abstract     = {{<p>The rapid progression of the electrification of road transport in many countries urges the need to make informed decisions on the location and size of the required charging infrastructure. This paper’s main contribution is a novel method to position fast-charging stations based on the transportation energy demand and to evaluate the performance of such charging infrastructure. Depending on their range and the availability of charging infrastructure, electric vehicles may need to adjust their route patterns to include en-route charging. Understanding and planning for these adjustments can help assess future charging infrastructure needs more effectively. The proposed method introduces a detailed agent-based simulation procedure to track individual trucks assumed to be fully electric. The procedure allows for analyzing each vehicle’s and charging station’s specific power flows. A case study based on a one-to-one representation of Swedish long-haul road freight transport is created based on real-world data. The results demonstrate that using the presented method, 90% of the Swedish long-haul truck fleet can be electrified with 26 carefully placed charging stations. These stations vary in size between 10-60 MW, presenting a utilization of 30-53%. The paper also provides detailed time variations in charging needs, using the best available data.</p>}},
  author       = {{Ingelstrom, Mattias and Arabani, Hamoun Pourroshanfekr and Alakula, Mats and Marquez-Fernandez, Francisco J.}},
  issn         = {{2332-7782}},
  keywords     = {{Agent-based modeling; Battery electric trucks; Charging infrastructure; Road transport-power grid interaction; Transport decarbonization; Zero-emission road freight transport}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Transportation Electrification}},
  title        = {{Placement of Fast-Charging Infrastructure for Long-Haul Road Freight Based on Spatio-Temporal Evaluation of En-Route Energy Needs}},
  url          = {{http://dx.doi.org/10.1109/TTE.2025.3610257}},
  doi          = {{10.1109/TTE.2025.3610257}},
  year         = {{2025}},
}