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Fuel-Efficient Control of Merging Maneuvers for Heavy-Duty Vehicle Platooning
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-5194-3306
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9940-5929
2015 (English)In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, IEEE conference proceedings, 2015, 1702-1707 p.Conference paper (Refereed)Text
Abstract [en]

The formation of groups of closely-spaced heavy-duty vehicles, known as platoons, reduces the overall aerodynamic drag and therefore leads to reduced fuel consumption and reduced greenhouse gas emissions. This paper focuses on the optimal control of merging maneuvers for the formation of a growing platoon. Hereto, the merging problem is formulated as a hybrid optimal control problem and an algorithm for the computation of optimal merging times and corresponding optimal vehicle trajectories is developed by exploiting an extension of Pontryagin's maximum principle. Moreover, a model predictive control approach on the basis of this algorithm is presented that makes the merging maneuvers robust to modelling uncertainties and external disturbances. The results are illustrated by evaluating a scenario involving three vehicles, which indicates fuel savings of up to 13% with respect to the vehicles driving alone.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 1702-1707 p.
Keyword [en]
Aerodynamic drag, Fuel economy, Fuels, Gas emissions, Greenhouse gases, Intelligent systems, Intelligent vehicle highway systems, Merging, Model predictive control, Optimal control systems, Transportation, Uncertainty analysis, Efficient control, External disturbances, Heavy duty vehicles, Hybrid optimal control, Model-predictive control approach, Optimal controls, Optimal vehicles, Pontryagin's maximum principle, Vehicles
National Category
Transport Systems and Logistics Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-181128DOI: 10.1109/ITSC.2015.276ISI: 000376668801122ScopusID: 2-s2.0-84950241369ISBN: 9781467365956ISBN: 9781467365956ISBN: 9781467365956ISBN: 9781467365956OAI: oai:DiVA.org:kth-181128DiVA: diva2:902084
Conference
18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015, 15 September 2015 through 18 September 2015
Note

QC 20160210

Available from: 2016-02-10 Created: 2016-01-29 Last updated: 2016-06-27Bibliographically approved

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Koller, Julian Phillip JohannGrossmann Colin, AlexBesselink, BartJohansson, Karl Henrik
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Automatic ControlACCESS Linnaeus Centre
Transport Systems and LogisticsEnergy Engineering

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