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Look-ahead Control of Heavy Vehicles
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology. (Vehicular Systems)
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Trucks are responsible for the major part of inland freight and so, they are a backbone of the modern economy but they are also a large consumer of energy. In this context, a dominating vehicle is a truck with heavy load on a long trip. The aim with look-ahead control is to reduce the energy consumption of heavy vehicles by utilizing information about future conditions focusing on the road topography ahead of the vehicle.

The possible gains with look-ahead control are evaluated by performing experiments with a truck on highway. A real-time control system based on receding horizon control (RHC) is set up where the optimization problem is solved repeatedly on-line for a certain horizon ahead of the vehicle. The experimental results show that significant reductions of the fuel consumption are achieved, and that the controller structure, where the algorithm calculates set points fed to lower level controllers, has satisfactory robustness to perform well on-board in a real environment. Moreover, the controller behavior has the preferred property of being intuitive, and the behavior is perceived as comfortable and natural by participating drivers and passengers.

A well-behaved and efficient algorithm is developed, based on dynamic programing, for the mixed-integer nonlinear minimum-fuel problem. A modeling framework is formulated where special attention is given to properly include gear shifting with physical models. Fuel equivalents are used to reformulate the problem into a tractable form and to construct a residual cost enabling the use of a shorter horizon ahead of the vehicle. Analysis of errors due to discretization of the continuous dynamics and due to interpolation shows that an energy formulation is beneficial for reducing both error sources. The result is an algorithm giving accurate solutions with low computational effort for use in an on-board controller for a fuel-optimal velocity profile and gear selection.

The prevailing approach for the look-ahead problem is RHC where main topics are the approximation of the residual cost and the choice of the horizon length. These two topics are given a thorough investigation independent of the method of solving the optimal control problem in each time step. The basis for the fuel equivalents and the residual cost is formed from physical intuition as well as mathematical interpretations in terms of the Lagrange multipliers used in optimization theory. Measures for suboptimality are introduced that enables choosing horizon length with the appropriate compromise between fuel consumption and trip time.

Control of a hybrid electric powertrain is put in the framework together with control of velocity and gear. For an efficient solution of the minimum-fuel problem in this case, more fuel equivalence factors and an energy formulation are employed. An application is demonstrated in a design study where it is shown how the optimal trade-off between size and capacity of the electrical system depends on road characteristics, and also that a modestly sized electrical system achieves most of the gain.

The contributions develop algorithms, create associated design tools, and carry out experiments. Altogether, a feasible framework is achieved that pave the way for on-board fuel-optimal look-ahead control.

Place, publisher, year, edition, pages
Linköping: Linköping University , 2010. , 16 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1315
Keyword [en]
automotive control, dynamic programming, predictive control, fuel-optimal control, long haulage truck
National Category
Engineering and Technology Computer and Information Science Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-54922ISBN: 978-91-7393-389-6 (print)OAI: oai:DiVA.org:liu-54922DiVA: diva2:311575
Public defence
2010-05-26, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2010-04-26 Created: 2010-04-22 Last updated: 2010-04-26Bibliographically approved
List of papers
1. Look-ahead control for heavy trucks to minimize trip time and fuel consumption
Open this publication in new window or tab >>Look-ahead control for heavy trucks to minimize trip time and fuel consumption
2009 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 17, no 2, 245-254 p.Article in journal (Refereed) Published
Abstract [en]

The scenario studied is a drive mission for a heavy diesel truck. With aid of an on board road slope database in combination with a GPS unit, information about the road geometry ahead is extracted. This look-ahead information is used in an optimization of the velocity trajectory with respect to a criterion formulation that weighs trip time and fuel consumption. A dynamic programming algorithm is devised and used in a predictive control scheme by constantly feeding the conventional cruise controller with new set points. The algorithm is evaluated with a real truck on a highway, and the experimental results show that the fuel consumption is significantly reduced.

Keyword
predictive control, dynamic programming, fuel-optimal control
National Category
Engineering and Technology Computer and Information Science Control Engineering
Identifiers
urn:nbn:se:liu:diva-16629 (URN)10.1016/j.conengprac.2008.07.005 (DOI)
Projects
CADICS
Note

Original Publication: Erik Hellström, Maria Ivarsson, Jan Åslund and Lars Nielsen, Look-ahead control for heavy trucks to minimize trip time and fuel consumption, 2009, Control Engineering Practice, (17), 2, 245-254. http://dx.doi.org/10.1016/j.conengprac.2008.07.005 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/

Available from: 2009-02-08 Created: 2009-02-06 Last updated: 2017-12-14
2. Design of an efficient algorithm for fuel-optimal look-ahead control
Open this publication in new window or tab >>Design of an efficient algorithm for fuel-optimal look-ahead control
2010 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 18, no 11, 1318-1327 p.Article in journal (Refereed) Published
Abstract [en]

A fuel-optimal control algorithm is developed for a heavy diesel truck that utilizes information about the road topography ahead of the vehicle when the route is known. A prediction model is formulated where special attention is given to properly include gear shifting. The aim is an algorithm with sufficiently low computational complexity. To this end, a dynamic programming algorithm is tailored, and complexity and numerical errors are analyzed. It is shown that it is beneficial to formulate the problem in terms of kinetic energy in order to avoid oscillating solutions and to reduce linear interpolation errors. A residual cost is derived from engine and driveline characteristics. The result is an on-board controller for an optimal velocity profile and gear selection.

Place, publisher, year, edition, pages
Elsevier, 2010
Keyword
automotive control, long haulage truck, dynamic programming, predictive control
National Category
Engineering and Technology Computer and Information Science Control Engineering
Identifiers
urn:nbn:se:liu:diva-54917 (URN)10.1016/j.conengprac.2009.12.008 (DOI)000284670800009 ()
Projects
CADICS
Note

Original Publication: Erik Hellström, Jan Åslund and Lars Nielsen, Design of an efficient algorithm for fuel-optimal look-ahead control, 2010, Control Engineering Practice. http://dx.doi.org/10.1016/j.conengprac.2009.12.008 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/

Available from: 2010-04-22 Created: 2010-04-21 Last updated: 2017-12-12
3. Horizon length and fuel equivalents for fuel-optimal look-ahead control
Open this publication in new window or tab >>Horizon length and fuel equivalents for fuel-optimal look-ahead control
2010 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Recent studies from several authors show that it is possible to lower the fuel consumption for heavy trucks by utilizing information about the road topography ahead of the vehicle. The approach in these studies is receding horizon control where horizon length and residual cost are main topics. To approach these topics, fuel equivalents previously introduced based on physical intuition are given a mathematical interpretation in terms of Lagrange multipliers. Measures for the suboptimality, caused by the truncated horizon and the residual cost approximation, are defined and evaluated for different routes and parameters.

Keyword
automotive control, intelligent cruise control, multipliers, predictive control
National Category
Engineering and Technology Computer and Information Science Control Engineering
Identifiers
urn:nbn:se:liu:diva-54920 (URN)10.3182/20100712-3-DE-2013.00114 (DOI)978-390266172-2 (ISBN)
Conference
6th IFAC Symposium Advances in Automatic Control, 12 - 14 July, Munich, Germany
Note

Original Publication: Erik Hellström, Jan Åslund and Lars Nielsen, Horizon length and fuel equivalents for fuel-optimal look-ahead control, 2010, 6th IFAC Symposium Advances in Automatic Control. Copyright: INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL IFAC.

Available from: 2010-04-22 Created: 2010-04-22 Last updated: 2014-09-22
4. Management of kinetic and electric energy in heavy trucks
Open this publication in new window or tab >>Management of kinetic and electric energy in heavy trucks
2010 (English)In: Transmission and Driveline, 2010, SAE International , 2010Conference paper, Published paper (Refereed)
Abstract [en]

Hybridization and velocity management are two important techniques for energy efficiency that mainly have been treated separately. Here they are put in a common framework that from the hybridization perspective can be seen as an extension of the equivalence factor idea in the well known strategy ECMS. From the perspective of look-ahead control, the extension is that energy can be stored not only in kinetic energy, but also electrically. The key idea is to introduce more equivalence factors in a way that enables efficient computations, but also so that the equivalence factors have a physical interpretation. The latter fact makes it easy to formulate a good residual cost to be used at the end of the look-ahead horizon. The formulation has different possible uses, but it is here applied on an evaluation of the size of the electrical system. Previous such studies, for e.g. ECMS, have typically used a driving cycle, i.e. a fixed velocity profile, but here the extra freedom to choose an optimal driving pattern is added.

Place, publisher, year, edition, pages
SAE International, 2010
Keyword
automotive control, predictive control, fuel-optimal control, hybrid electric vehicles, energy management
National Category
Engineering and Technology Computer and Information Science Control Engineering
Identifiers
urn:nbn:se:liu:diva-54921 (URN)10.4271/2010-01-1314 (DOI)978-0-7680-3425-7 (ISBN)
Conference
SAE 2010 World Congress & Exhibition, April 2010, Detroit, MI, USA, Session: Transmission and Driveline: Hybrid
Projects
CADICS
Available from: 2010-04-22 Created: 2010-04-22 Last updated: 2012-10-01

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