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  • 1.
    Fröberg, Anders
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Hellström, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Explicit Fuel Optimal Speed Profiles for Heavy Trucks on a Set of Topograhic Road Profiles2006In: Electronic Engine Controls, SAE World Congress 2006, 2006Conference paper (Refereed)
    Abstract [en]

    The problem addressed is how to drive a heavy truck over various road topographies such that the fuel consumption is minimized. Using a realistic model of a truck powertrain, an optimization problem for minimization of fuel consumption is formulated. Through the solutions of this problem optimal speed profiles are found. An advantage here is that explicit analytical solutions can be found, and this is done for a few constructed test roads. The test roads are constructed to be easy enough to enable analytical solutions but still capture the important properties of real roads. In this way the obtained solutions provide explanations to some behavior obtained by ourselves and others using more elaborate modelling and numeric optimization like dynamic programming.

    The results show that for level road and in small gradients the optimal solution is to drive with constant speed. For large gradients in downhill slopes it is optimal to utilize the kinetic energy of the vehicle to accelerate in order to gain speed. This speed increase is used to lower the speed on other road sections such that the total average speed is kept. Taking account for limitations of top speed the optimal speed profile changes to a strategy that minimizes brake usage. This is done by, e.g., slowing down before steep down gradients where the truck will accelerate even though the engine does not produce any torque.

  • 2.
    Fröberg, Anders
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Hellström, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nielsen, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Explicit Fuel Optimal Speed Profiles for Heavy Trucks on a Set of Topographic Road Profiles2006In: SAE World Congress 2006,2006, SAE , 2006Conference paper (Refereed)
    Abstract [en]

     The problem addressed is how to drive a heavy truck over various road topographies such that the fuel consumption is minimized. Using a realistic model of a truck powertrain, an optimization problem for minimization of fuel consumption is formulated. Through the solutions of this problem optimal speed profiles are found. An advantage here is that explicit analytical solutions can be found, and this is done for a few constructed test roads. The test roads are constructed to be easy enough to enable analytical solutions but still capture the important properties of real roads. In this way the obtained solutions provide explanations to some behaviour obtained by ourselves and others using more elaborate modeling and numeric optimization like dynamic programming. The results show that for level road and in small gradients the optimal solution is to drive with constant speed. For large gradients in downhill slopes it is optimal to utilize the kinetic energy of the vehicle to accelerate in order to gain speed. This speed increase is used to lower the speed on other road sections such that the total average speed is kept. Taking account for limitations of top speed the optimal speed profile changes to a strategy that minimizes brake usage. This is done by e.g. slowing down before steep down gradients were the truck will accelerate even though the engine does not produce any torque.

  • 3.
    Hellström, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Look-ahead Control of Heavy Trucks utilizing Road Topography2007Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The power to mass ratio of a heavy truck causes even moderate slopes to have a significant influence on the motion. The velocity will inevitable vary within an interval that is primarily determined by the ratio and the road topography. If further variations are actuated by a controller, there is a potential to lower the fuel consumption by taking the upcoming topography into account. This possibility is explored through theoretical and simulation studies as well as experiments in this work.

    Look-ahead control is a predictive strategy that repeatedly solves an optimization problem online by means of a tailored dynamic programming algorithm. The scenario in this work is a drive mission for a heavy diesel truck where the route is known. It is assumed that there is road data on-board and that the current heading is known. A look-ahead controller is then developed to minimize fuel consumption and trip time.

    The look-ahead control is realized and evaluated in a demonstrator vehicle and further studied in simulations. In the prototype demonstration, information about the road slope ahead is extracted from an on-board database in combination with a GPS unit. The algorithm calculates the optimal velocity trajectory online and feeds the conventional cruise controller with new set points. The results from the experiments and simulations confirm that look-ahead control reduces the fuel consumption without increasing the travel time. Also, the number of gear shifts is reduced. Drivers and passengers that have participated in tests and demonstrations have perceived the vehicle behavior as comfortable and natural.

  • 4.
    Hellström, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Look-ahead Control of Heavy Vehicles2010Doctoral 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.

    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, p. 245-254Article 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.

    Keywords
    predictive control, dynamic programming, fuel-optimal control
    National Category
    Engineering and Technology Computer and Information Sciences 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: 2018-01-13
    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, p. 1318-1327Article 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
    Keywords
    automotive control, long haulage truck, dynamic programming, predictive control
    National Category
    Engineering and Technology Computer and Information Sciences 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: 2018-01-12
    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.

    Keywords
    automotive control, intelligent cruise control, multipliers, predictive control
    National Category
    Engineering and Technology Computer and Information Sciences 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: 2018-01-12
    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
    Keywords
    automotive control, predictive control, fuel-optimal control, hybrid electric vehicles, energy management
    National Category
    Engineering and Technology Computer and Information Sciences 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: 2018-01-12
  • 5.
    Hellström, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    A Real-Time Fuel-Optimal Cruise Controller for Heavy Trucks using Road Topography Information2006In: SAE World Congress, 2006Conference paper (Refereed)
    Abstract [en]

    New and exciting possibilities in vehicle control are revealed by the consideration of topography, for example through the combination of GPS and three-dimensional road maps. How information about future road slopes can be utilized in a heavy truck is explored. The aim is set at reducing the fuel consumption over a route without increasing the total travel time.

    A model predictive control (MPC) scheme is used to control the longitudinal behavior of the vehicle, which entails determining accelerator and brake levels and also which gear to engage. The optimization is accomplished through discrete dynamic programming. A cost function that weighs fuel use, negative deviations from the reference velocity, velocity changes, gear shifts and brake use is used to define the optimization criterion.

    Computer simulations back and forth on 127 km of a typical highway route in Sweden show that the fuel consumption in a heavy truck can be reduced 2.5% with a negligible change in travel time.

  • 6.
    Hellström, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Ivarsson, Maria
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nielsen, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Look-ahead Control for Heavy Trucks to minimize Trip Time and Fuel Consumption2007In: Fifth IFAC Symposium on Advances in Automotive Control,2007, 2007Conference paper (Refereed)
  • 7.
    Hellström, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Ivarsson, Maria
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Look-ahead control for heavy trucks to minimize trip time and fuel consumption2009In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 17, no 2, p. 245-254Article in journal (Refereed)
    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.

  • 8.
    Hellström, Erik
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Nielsen, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Design of a Well-behaved Algorithm for On-board Look-ahead Control2008In: IFAC World Congress,2008, 2008Conference paper (Refereed)
    Abstract [en]

    A look-ahead controller is developed for a heavy diesel truck that utilizes information about the road topography ahead of the vehicle when the route is known. A dedicated prediction model is formulated where special attention is given to properly include gear shifting. The nature of the problem is analyzed for the purpose of optimization, and a well performing dynamic programming algorithm is tailored. A key step for satisfactory solutions with a sufficiently low computational effort is to avoid numerical problems. The focus here is the choice of discretization method, and it turns out that a basic analysis give decisive insight into the interplay between the criterion and the discretization errors. The resulting algorithm is demonstrated to perform well in real on-line tests on a highway.

  • 9.
    Hellström, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Design of an efficient algorithm for fuel-optimal look-ahead control2010In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 18, no 11, p. 1318-1327Article in journal (Refereed)
    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.

  • 10.
    Hellström, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Horizon length and fuel equivalents for fuel-optimal look-ahead control2010Conference 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.

  • 11.
    Hellström, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Management of kinetic and electric energy in heavy trucks2010In: Transmission and Driveline, 2010, SAE International , 2010Conference 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.

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