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Distributed Charging Coordination of Electric Trucks with Limited Charging Resources
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9488-9143
School of Computing and Augmented Intelligence, Arizona State University, Tempe, The United States, AZ-85281.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.ORCID iD: 0000-0001-9940-5929
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-3672-5316
2024 (English)In: 2024 European Control Conference, ECC 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 2897-2902Conference paper, Published paper (Refereed)
Abstract [en]

Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial. As charging resources are limited, waiting times for some trucks can be prolonged at certain stations. To facilitate the efficient operation of electric trucks, we propose a distributed charging coordination framework. Within the scheme, the charging stations provide waiting estimates to incoming trucks upon request and assign charging ports according to the first-come, first-served rule. Based on the updated information, the individual trucks compute where and how long to charge whenever approaching a charging station in order to complete their delivery missions timely and cost-effectively. We perform empirical studies for trucks traveling over the Swedish road network and compare our scheme with the one where charging plans are computed offline, assuming unlimited charging facilities. It is shown that the proposed scheme outperforms the offline approach at the expense of little communication overhead.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 2897-2902
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-351930DOI: 10.23919/ECC64448.2024.10590837ISI: 001290216502108Scopus ID: 2-s2.0-85200596068OAI: oai:DiVA.org:kth-351930DiVA, id: diva2:1890146
Conference
2024 European Control Conference, ECC 2024, Stockholm, Sweden, Jun 25 2024 - Jun 28 2024
Note

QC 20250428

Available from: 2024-08-19 Created: 2024-08-19 Last updated: 2025-04-28Bibliographically approved

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Bai, TingJohansson, Karl H.Mårtensson, Jonas

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Integrated Transport Research Lab, ITRLDecision and Control Systems (Automatic Control)ACCESS Linnaeus Centre
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