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Optimal Speed and Gear Shift Control of Long-haulage Trucks
RISE - Research Institutes of Sweden, ICT, Viktoria. Linköping University, Sweden.
RISE - Research Institutes of Sweden, ICT, Viktoria.ORCID iD: 0000-0003-0709-4954
AB Volvo, Sweden.
AB Volvo, Sweden.
2019 (English)In: IFAC-PapersOnLine, Elsevier B.V. , 2019, no 5, p. 471-477Conference paper, Published paper (Refereed)
Abstract [en]

Long haulage trucks consume large amounts of fuel, and fuel savings are desired both from economical and environmental aspects. When the upcoming road topology is known, the speed and gear shifts can be optimized in order to minimize the fuel consumption by e.g. minimizing the braking of the truck. Three different optimal control approaches are evaluated and compared for the speed and gear shift optimization problem. The results are based on simulations, but two of the three evaluated solvers are also implemented on-board a truck using rapid prototyping to investigate the feasibility of such systems. The results indicate that optimal control of the speed reduces the fuel consumption more than finding the optimal gear shift trajectory. The overall optimization problem contains one discrete and one continuous state, which makes the selection of optimization method complex. A sequential optimization scheme where the optimal speed profile is found using linear programming and the optimal gear profile is found using dynamic programming shows similar results as using dynamic programming for the overall problem simultaneously. One drawback with this solution is robustness and several tuning parameters. The driveability of the solutions are found good at the performed on-board tests. 

Place, publisher, year, edition, pages
Elsevier B.V. , 2019. no 5, p. 471-477
Keywords [en]
dynamic programming, fuel-optimal control, intelligent cruise control, linear programming, Adaptive cruise control, Fuel economy, Fuels, Speed, Trucks, Continuous state, Environmental aspects, Fuel optimal, Optimal controls, Optimization method, Optimization problems, Sequential optimization, Tuning parameter
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-42367DOI: 10.1016/j.ifacol.2019.09.075Scopus ID: 2-s2.0-85076094913OAI: oai:DiVA.org:ri-42367DiVA, id: diva2:1381248
Conference
9th IFAC Symposium on Advances in Automotive Control, AAC 2019, 23 June 2019 through 27 June 2019
Available from: 2019-12-20 Created: 2019-12-20 Last updated: 2019-12-20Bibliographically approved

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Voronov, Alexey

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