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Improving fuel economy of heavy-duty vehicles in daily driving

  • Chaozhe R. He
  • , Anil Alan
  • , Tamas G. Molnar
  • , Sergei S. Avedisov
  • , A. Harvey Bell
  • , Russell Zukouski
  • , Matthew Hunkler
  • , Jim Yan
  • , Gabor Orosz
  • University of Michigan, Ann Arbor
  • Navistar Internal Corporation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In this work, we integrate two once separate concepts for longitudinal control of heavy duty vehicles: responding to elevation changes to improve fuel economy using preview and reacting to the motion of preceding vehicles using feedback. The two concepts are unified to provide a safe yet fuel efficient connected and automated technology for heavy duty vehicles. First, we establish an integrated control framework of the two concepts based on barrier function theory and then we discuss the detailed control design of each concept. Finally, we demonstrate the benefits of the proposed design against a naive switching controller by experimentally evaluating the performance of a connected automated truck.

Original languageEnglish
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2306-2311
Number of pages6
ISBN (Electronic)9781538682661
DOIs
StatePublished - Jul 2020
Event2020 American Control Conference, ACC 2020 - Virtual, Online, United States
Duration: Jul 1 2020Jul 3 2020

Publication series

NameProceedings of the American Control Conference
Volume2020-July
ISSN (Print)0743-1619

Conference

Conference2020 American Control Conference, ACC 2020
Country/TerritoryUnited States
CityVirtual, Online
Period07/1/2007/3/20

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