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Optimal Speed Trajectories Under Variations in the Driving Corridor
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Scania CV AB, Sweden.ORCID iD: 0000-0003-2923-986X
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.ORCID iD: 0000-0002-3672-5316
2017 (English)In: IFAC-PapersOnLine, Elsevier, 2017, Vol. 50, p. 12551-12556Conference paper, Published paper (Refereed)
Abstract [en]

The optimal speed trajectory for a heavy-duty truck is calculated using the Pontryagin's maximum principle. The truck motion depends on controllable tractive and braking forces and external forces such as air and rolling resistance and road slope. The velocity of the vehicle is restricted to be within a driving corridor which consists of an upper and a lower boundary. Simulations are performed on data from a test cycle commonly used for testing distribution driving. The data include road slope and a speed reference, from which the driving corridor is created automatically. The simulations include a sensitivity analysis on how changes in the parameters for the driving corridor influence the energy consumption and trip time. For the widest driving corridor tested, 15.8% energy was saved compared to the most narrow corridor without increasing the trip time. Most energy was saved by reducing the losses due to braking and small amounts of energy were saved by reducing the losses due to air resistance. Finally, optimal trajectories with the same trip time derived from different settings on the driving corridor are compared in order to analyse energy efficient driving patterns.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 50, p. 12551-12556
Keyword [en]
Nonlinear and optimal automotive control, Trajectory and Path Planning, Intelligent driver aids
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-216960DOI: 10.1016/j.ifacol.2017.08.2194Scopus ID: 2-s2.0-85044266406OAI: oai:DiVA.org:kth-216960DiVA, id: diva2:1152605
Conference
IFAC 2017 World Congress
Funder
VINNOVA
Note

QC 20171215

Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2017-12-15Bibliographically approved

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