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How optimization-driven planning enables large-scale electrification of heavy-duty freight
Linköping University, Department of Management and Engineering, Production Economics.ORCID iD: 0009-0002-6559-2898
Einride.ORCID iD: 0000-0001-7324-6691
Einride.
Fraunhofer-Institut für System- und Innovationsforschung ISI.ORCID iD: 0000-0002-0332-3943
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2025 (English)Conference paper, Published paper (Refereed)
Sustainable development
Fossil fuels, Climate Improvements
Place, publisher, year, edition, pages
2025.
Keywords [en]
Heavy Duty Electric Vehicles, Intelligent Transportation Systems for EVs, Modeling and Simulation
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:liu:diva-215863OAI: oai:DiVA.org:liu-215863DiVA, id: diva2:1979864
Conference
38th International Electric Vehicle Symposium and Exhibition (EVS38)
Available from: 2025-07-01 Created: 2025-07-01 Last updated: 2025-07-01

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Zackrisson, Anton

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Zackrisson, AntonEngholm, AlbinLink, SteffenPlötz, Patrick
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Total: 133 hits
CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
  • rtf
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