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Data-driven analysis of strategic–operational interfaces in freight electrification under deep uncertainty
Department of Management and Engineering, Linköping University, 581 83 Linköping, Sweden; Einride AB, Regeringsgatan 65, 111 56 Stockholm, Sweden, Regeringsgatan 65.
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Einride AB, Regeringsgatan 65, 111 56 Stockholm, Sweden, Regeringsgatan 65; Integrated Transport Research Lab, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden.ORCID iD: 0000-0001-7324-6691
Department of Management and Engineering, Linköping University, 581 83 Linköping, Sweden.
2025 (English)In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 139, article id 104524Article in journal (Refereed) Published
Abstract [en]

Battery electric trucks (BETs) offer environmental benefits but have been challenged by technical and economic viability compared to internal combustion engine trucks (ICETs). Meanwhile, fleet owner-operators have difficulties making strategic decisions of freight electrification based on Total Cost-of-Ownership (TCO) due to inaccurate representations of fleet operations, high uncertainty, and lack of generalizability. We therefore develop a data-driven analytical framework for BET and ICET fleets evaluating over 100,000 scenarios to measure the effects of strategic decisions, operational optimization, and deep uncertainty on TCO and competitiveness. We find that electrification becomes more efficient at scale, enabling optimization of routing, charging and scheduling to better mitigate operational constraints, thus improving service level and utilization. Partial electrification in large networks shows to be a robust pathway towards uncertainties such as battery prices and future battery technology. The study results provide guidelines for fleet operators realizing electrification and thereby their sustainability goals in operations.

Place, publisher, year, edition, pages
Elsevier BV , 2025. Vol. 139, article id 104524
Keywords [en]
Battery electric trucks, Decision making under deep uncertainty (DMDU), Freight electrification, Heavy-duty trucks, Sobol variance decomposition, Strategic–operational interfaces
National Category
Other Mechanical Engineering Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-357914DOI: 10.1016/j.trd.2024.104524ISI: 001374626000001Scopus ID: 2-s2.0-85211026482OAI: oai:DiVA.org:kth-357914DiVA, id: diva2:1922621
Note

QC 20250113

Available from: 2024-12-19 Created: 2024-12-19 Last updated: 2025-01-13Bibliographically approved

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Engholm, Albin

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