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  • 1.
    Nilsson, Tomas
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Engine Operation in a Multi-Mode CVT Wheel Loader2012Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Throughout the vehicular industry there is a drive for increased fuel efficiency. This is the case also for heavy equipment like wheel loaders. The operation of such machines is characterized by its highly transient nature, the episodes of high tractive effort at low speed and that power is used by both the transmission and the working hydraulics. The present transmission is well suited for this operation, though the efficiency is low in some modes of operation. Both operational advantages and efficiency drawbacks are highly related to the use of a torque converter. Continuously variable transmissions (CVTs) may hold a potential for achieving similar operability with reduced fuel consumption, though such devices increase the demand for, and importance of, active control.

    Common wheel loader operation is readily described in a framework of loading cycles. The general loading cycle is described, and a transmission oriented cycle description is introduced, in deterministic and stochastic forms, and a description is made on how such cycles are created from measurements. A loading cycle identifier is used for detecting cycles in a set of measured data, and a stochastic cycle is formed from statistics on the detected cycles.

    CVTs increase the possibility for active control, since a degree of freedom is introduced in the engine operating point. Optimal operating point trajectories are derived, using dynamic programming (DP), for naturally aspirated (NA) and turbocharged (TC) engines. The NA-engine solution is analyzed with Pontryagin’s maximum principle (PMP). This analysis is used for deriving PMP based methods for finding the optimal solutions for both engines. Experience show that these methods are 100 times faster than DP, but since the restrictions on the applicable load cases are severe, the main contribution from these is in the pedagogic visualization of optimization. Methods for deriving suboptimal operating point trajectories for both the NA and the TC engines are also developed, based on the optimization results. The methods are a factor >1000 faster than DP while producing feasible trajectories with less than 5% increase in fuel consumption compared to the optimal.

    Multi-mode CVTs provide the possibility of even higher efficiency than single mode devices. At the same time, the added complexity makes control development increasingly time consuming and costly, while the quality of the control is decisive for the success of the system. It is therefore important to be able to evaluate the potential of transmission concepts before control development commence. Stochastic dynamic programming is used and evaluated as a tool for control independent comparing of the present transmission and a hydrostatic multi-mode CVT concept. The introduction of a stochastic load complicates the optimization, especially in the feasible choice of states for the optimization. The results show that the multi-mode CVT has at least 15% lower minimum fuel consumption than the present transmission, and that this difference is not sensitive to prediction uncertainties.

  • 2.
    Nilsson, Tomas
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Predictive Control of Wheel Loader Transmissions2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The transmissions of present heavy wheel loaders are in general based on torque converters. The characteristics of this component suits these machines, especially in that it enables thrust from zero vehicle speed without risk of stalling the engine, without active control. Unfortunately, the component also causes losses which might become large compared to the transmitted power. One approach for mitigating these losses is to switch to a continuously variable transmission. Changing to such a system greatly increases the possibility, and the need, for actively selecting the engine speed, and here a conflict emerges. A low engine speed is desired for high efficiency but a high speed is required for high power.

    Heavy wheel loaders often operate according to a common repeating pattern known as the short loading cycle. This cycle is extremely transient, which makes the choice of engine operating point both important and difficult. At the same time, the repeating pattern in the operation enables a rough prediction of the future operation. One way to use the uncertain prediction is to use optimization techniques for selecting the best control actions. This requires a method for detecting the operational pattern and producing a prediction from this, to formulate a manageable optimization problem, and for solving this, and finally to actually control the machine according to the optimization results. This problem is treated in the four papers that are included in this dissertation.

    The first paper describes a method for automatically detecting when the machine is operating according to any of several predefined patterns. The detector uses events and automata descriptions of the cycles, which makes the method simple yet powerful. In the evaluations over 90% of the actual cycles are detected and correctly identified. The detector also enables a quick analysis of large datasets. In several of the following papers this is used to condense measured data sequences into statistical cycles for the control optimization.

    In the second paper dynamic programming and Pontryagin’s maximum principle is applied to a simplified system consisting of a diesel engine and a generator. Methods are developed based on the maximum principle analysis, for finding the fuel optimal trajectories at output power steps, and the simplicity of the system enables a deeper analysis of these solutions. The methods are used to examine and visualize the mechanisms behind the solutions at power transients, and the models form the basis for the models in the following papers.

    The third paper describes two different concepts for implementing dynamic programming based optimal control of a hydrostatic transmission. In this system one load component forms a stochastic state constraint, and the concepts present two different strategies for handling this constraint. The controller concepts are evaluated through simulations, in terms of implementability, robustness against uncertainties in the prediction and fuel savings.

    The fourth paper describes the implementation and testing of a predictive controller, based on stochastic dynamic programming, for the engine and generator in a diesel electric powertrain. The controller is evaluated through both simulations and field tests, with several drivers, at a realistic work site, thus including all relevant disturbances and uncertainties. The evaluations indicate a ∼ 5% fuel benefit of utilizing a cycle prediction in the controller.

    List of papers
    1. Robust Driving Pattern Detection and Identification with a Wheel Loader Application
    Open this publication in new window or tab >>Robust Driving Pattern Detection and Identification with a Wheel Loader Application
    Show others...
    2014 (English)In: International journal of vehicle systems modelling and testing, ISSN 1745-6436, Vol. 9, no 1, p. 56-76Article in journal (Refereed) Published
    Abstract [en]

    Information about wheel loader usage can be used in several ways to optimize customer adaption. First, optimizing the configuration and component sizing of a wheel loader to customer needs can lead to a significant improvement in e.g. fuel efficiency and cost. Second, relevant driving cycles to be used in the development of wheel loaders can be extracted from usage data. Third, on-line usage identification opens up for the possibility of implementing advanced look-ahead control strategies for wheel loader operation. The main objective here is to develop an on-line algorithm that automatically, using production sensors only, can extract information about the usage of a machine. Two main challenges are that sensors are not located with respect to this task and that significant usage disturbances typically occur during operation. The proposed method is based on a combination of several individually simple techniques using signal processing, state automaton techniques, and parameter estimation algorithms. The approach is found to berobust when evaluated on measured data of wheel loaders loading gravel and shot rock.

    Place, publisher, year, edition, pages
    InderScience Publishers, 2014
    Keywords
    Driving cycle; Driving cycle identification; Driving pattern; Pattern identification; Robust detection; State automaton; Usage classification; Usage detection; Wheel loader
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-92222 (URN)10.1504/IJVSMT.2014.059156 (DOI)2-s2.0-84893958574 (Scopus ID)
    Available from: 2013-05-08 Created: 2013-05-08 Last updated: 2015-04-01Bibliographically approved
    2. Minimizing Fuel Use During Power Transients for Naturally Aspirated and Turbo Charged Diesel Engines
    Open this publication in new window or tab >>Minimizing Fuel Use During Power Transients for Naturally Aspirated and Turbo Charged Diesel Engines
    2014 (English)Report (Other academic)
    Abstract [en]

    Recent development has renewed the interest in drivetrain concepts which gives a higher degree offreedom by disconnecting the engine and vehicle speeds. This freedom raises the demand for activecontrol, which especially during transients is not trivial, but of which the quality is crucial for the successof the drivetrain concept. In this work the fuel optimal engine operating point trajectories for a naturallyaspirated and a turbocharged diesel engine, connected to a load which does not restrict the engine speed,is derived, analysed and utilized for finding a suboptimal operating point trajectory. The analysis andoptimization is made with dynamic programming, Pontryagin’s maximum principle and a suboptimalstrategy based on the static optimal operating points. Methods are derived for using Pontryagin’smaximum principle for finding the optimal operating point trajectories, for simple load cases. The timeneeded for computation is reduced a factor 1000−100, depending on engine layout, compared to dynamicprogramming. These methods are only applicable to very simple load cases though. Finally, a suboptimalcalculation method which reduce the time needed for computation a factor > 1000 compared to dynamicprogramming, while showing a < 5% increase in fuel consumption compared to the optimal, is presented.

    Publisher
    p. 13
    Series
    LiTH-ISY-R, ISSN 1400-3902 ; 3077
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-112720 (URN)LiTH-ISY-R-3077 (ISRN)
    Available from: 2014-12-09 Created: 2014-12-09 Last updated: 2015-01-19Bibliographically approved
    3. Development of look-ahead controller concepts for a wheel loader application: [Développement de concepts d’une commande prédictive, destinée à une application pour chargeur sur pneus]
    Open this publication in new window or tab >>Development of look-ahead controller concepts for a wheel loader application: [Développement de concepts d’une commande prédictive, destinée à une application pour chargeur sur pneus]
    2015 (English)In: Oil & gas science and technology, ISSN 1294-4475, E-ISSN 1953-8189, Vol. 70, no 1, p. 159-178Article in journal (Refereed) Published
    Abstract [en]

    This paper presents two conceptual methods, based on dynamic programming, for one-step look-ahead control of a Continuously Variable Transmission (CVT) in a wheel loader. The first method developed, designated Stochastic Dynamic Programming (SDP), uses a statistical load prediction and stochastic dynamic programming for minimizing fuel use. The second method developed, designated Free-Time Dynamic Programming (FTDP), has vehicle speed as a state and introduces a fixed 0.1 s delay in the bucket controls in a combined minimization of fuel and time. The methods are evaluated using a set of 34 measured loading cycles, used in a ‘leave one out’ manner.

    The evaluation shows that the SDP method requires about 1/10th of the computational effort of FTDP and has a more transparent impact of differences in the cycle prediction. The FTDP method, on the other hand, shows a 10% lower fuel consumption, which is close to the actual optimum, at the same cycle times, and is able to complete a much larger part of the evaluation cycles.

    Abstract [fr]

    Ce document présente deux méthodes de conception, basées sur la programmation dynamique, pour la commande à un pas de prédiction d’une transmission continûment variable (Continuously Variable Transmission, CVT) d’un chargeur sur pneus. La première méthode développée, appelée programmation dynamique stochastique (Stochastic Dynamic Programming, SDP) utilise une prédiction statistique de la charge et la programmation dynamique stochastique pour minimiser l’utilisation de carburant. La seconde méthode développée, appelée programmation dynamique à temps libre (Free-Time Dynamic Programming, FTDP), établit la vitesse du véhicule en tant qu’état et introduit un retard de 0:1 s dans les commandes du godet pour minimiser à la fois l’utilisation de carburant et le temps nécessaire à l’opération.

    Les méthodes sont évaluées en s’appuyant sur 34 cycles de chargement mesurés, utilisés selon la méthode de validation croisée « leave-one-out ».

    L’évaluation montre que la méthode SDP requiert environ 1 dixième de l’effort de calcul de la méthode FTDP, et qu’elle a un impact plus transparent sur les écarts dans la prédiction du cycle. D’un autre côté, avec la méthode FTDP on obtient une réduction de 10% de la consommation de carburant, ce qui est proche de l’optimum réel, pour les mêmes durées de cycle, et elle permet de réaliser une plus grande partie des cycles d’évaluation.

    Place, publisher, year, edition, pages
    EDITIONS TECHNIP, 2015
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-112719 (URN)10.2516/ogst/2014022 (DOI)000351444400011 ()
    Available from: 2014-12-09 Created: 2014-12-09 Last updated: 2017-12-05
    4. Predictive control of a diesel electric wheel loader powertrain
    Open this publication in new window or tab >>Predictive control of a diesel electric wheel loader powertrain
    2015 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 41, p. 47-56Article in journal (Refereed) Published
    Abstract [en]

    Wheel loaders often have a highly repetitive pattern of operation, which can be used for creating a rough prediction of future operation. As the present torque converter based transmission is replaced with an infinitely variable device, such as an electric or hydraulic transmission, a freedom in the choice of engine speed is introduced. This choice is far from trivial in the extremely transient operation of these machines, but the availability of a load prediction should be utilized.

    In this paper, a predictive engine and generator controller, based on stochastic dynamic programming, is described, implemented and evaluated. The evaluation is performed against non-predictive controllers in the same system, to lift out any possible benefits of utilizing the repetition based prediction. Simulations and field tests show that the controllers are able to handle disturbances introduced from model errors, the machine environment and the human operator, and that the predictive controller gives around 5% lower fuel consumption than the non-predictive reference controllers.

    Place, publisher, year, edition, pages
    Elsevier, 2015
    Keywords
    Diesel engine; Continuously variable transmission; Predictive control; Stochastic dynamic programming
    National Category
    Mechanical Engineering
    Identifiers
    urn:nbn:se:liu:diva-112891 (URN)10.1016/j.conengprac.2015.04.008 (DOI)000357546200005 ()
    Available from: 2014-12-19 Created: 2014-12-19 Last updated: 2017-12-05Bibliographically approved
  • 3.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden .
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Development of look-ahead controller concepts for a wheel loader application: [Développement de concepts d’une commande prédictive, destinée à une application pour chargeur sur pneus]2015In: Oil & gas science and technology, ISSN 1294-4475, E-ISSN 1953-8189, Vol. 70, no 1, p. 159-178Article in journal (Refereed)
    Abstract [en]

    This paper presents two conceptual methods, based on dynamic programming, for one-step look-ahead control of a Continuously Variable Transmission (CVT) in a wheel loader. The first method developed, designated Stochastic Dynamic Programming (SDP), uses a statistical load prediction and stochastic dynamic programming for minimizing fuel use. The second method developed, designated Free-Time Dynamic Programming (FTDP), has vehicle speed as a state and introduces a fixed 0.1 s delay in the bucket controls in a combined minimization of fuel and time. The methods are evaluated using a set of 34 measured loading cycles, used in a ‘leave one out’ manner.

    The evaluation shows that the SDP method requires about 1/10th of the computational effort of FTDP and has a more transparent impact of differences in the cycle prediction. The FTDP method, on the other hand, shows a 10% lower fuel consumption, which is close to the actual optimum, at the same cycle times, and is able to complete a much larger part of the evaluation cycles.

  • 4.
    Nilsson, Tomas
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden .
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Fuel and time minimization in a CVT wheel loader application2013In: IFAC Proceedings Volumes / [ed] Edward Boje, University of Cape Town, South Africa and Xiaohua Xia, University of Pretoria, South Africa, 2013, Vol. 46, p. 201-206Conference paper (Refereed)
    Abstract [en]

    A method is developed for the minimization of time and fuel required for performing a short loading cycle with a CVT wheel loader. A factor β is used for weighing time to fuel in the optimization. Dynamic programming is used as optimization algorithm, and the developed method is based on the change of independent variable, from time to distance driven. It is shown that a change of states from speeds to kinetic energies in the internal simulations is essential.

    A driving cycle, derived from measurements, representing a short loading cycle is introduced. Optimization is performed against this cycle according to the method presented, using two different values on the time to fuel weighing parameter. It is shown that this parameter can be used to find optimal solutions directed toward short time or low fuel consumption.

  • 5.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fuel Potential and Prediction Sensitivity of a Power-Split CVT in a Wheel Loader2012In: Proceedings of the 2012 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, 2012, p. 49-56Conference paper (Refereed)
    Abstract [en]

    Wheel loader transmissions are commonly based on a torque converter and an automatic gearbox. This solution is mechanically robust and well suited for the typical operation of the machine, but the fuel efficiency is low at some modes of operation. One proposed improvement is to replace the present transmission with a multi-mode power-split CVT (MM-CVT). This paper compares the fuel saving potential of the MM-CVT to the potential of the present transmission under different assumptions on the prediction of future loads. A load cycle with a probability distribution is created from a measurement including 34 short loading cycles. Trajectory optimization is performed both against this, probabilistic, and three deterministic load cycles with the two concepts. The optimization shows that the MM-CVT transmission has at least 15% better fuel saving potential than the present transmission, and that this difference is not sensitive to the quality of the prediction or the smoothness or length of the load case.

  • 6.
    Nilsson, Tomas
    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. Volvo Construction Equipment.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Minimizing Fuel Use During Power Transients for Naturally Aspirated and Turbo Charged Diesel Engines2014Report (Other academic)
    Abstract [en]

    Recent development has renewed the interest in drivetrain concepts which gives a higher degree offreedom by disconnecting the engine and vehicle speeds. This freedom raises the demand for activecontrol, which especially during transients is not trivial, but of which the quality is crucial for the successof the drivetrain concept. In this work the fuel optimal engine operating point trajectories for a naturallyaspirated and a turbocharged diesel engine, connected to a load which does not restrict the engine speed,is derived, analysed and utilized for finding a suboptimal operating point trajectory. The analysis andoptimization is made with dynamic programming, Pontryagin’s maximum principle and a suboptimalstrategy based on the static optimal operating points. Methods are derived for using Pontryagin’smaximum principle for finding the optimal operating point trajectories, for simple load cases. The timeneeded for computation is reduced a factor 1000−100, depending on engine layout, compared to dynamicprogramming. These methods are only applicable to very simple load cases though. Finally, a suboptimalcalculation method which reduce the time needed for computation a factor > 1000 compared to dynamicprogramming, while showing a < 5% increase in fuel consumption compared to the optimal, is presented.

  • 7.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    On the use of stochastic dynamic programming for evaluating a power-split CVT in a wheel loader2012In: Proceedigns of the 8th IEEE vehicle power and propulsion conference, IEEE , 2012, p. 840-845Conference paper (Refereed)
    Abstract [en]

    Complex transmission concepts may enable high fuel efficiency but require much effort in controller development. This effort should only be spent if the potential of the concept if high, a potential which can be determined using optimization techniques. This paper examine the use of stochastic dynamic programming for transmission potential evaluation, applied on a wheel loader. The concepts evaluated is the present automatic gearbox and a multi-mode CVT (MM-CVT). A probabilistic driving cycle is created from a measurement including 34 loading cycles. Trajectory optimization is performed both against probabilistic and deterministic cycles. The paper shows that the introduction of a probabilistic load highly affect the application of optimization. It is also shown that the MM-CVT has approximately 20% lower minimum fuel requirement than the present transmission, and that this number is not sensitive to the quality of the prediction.

  • 8.
    Nilsson, Tomas
    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.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Operation of a Turbocharged Diesel Engine during Transients2012In: SAE International Journal of Engines, ISSN 1946-3936, E-ISSN 1946-3944, Vol. 5, no 2, p. 571-578Article in journal (Refereed)
    Abstract [en]

    Recent development has renewed the interest in drivetrain concepts which give a higher degree of freedom by disconnecting the engine and vehicle speeds. This freedom raises the demand for active control, which especially during transients is not trivial but of which the quality is crucial for the success of the drivetrain concept. In this work the fuel optimal solution for a turbocharged diesel engine connected to a load which does not restrict the engine speed is derived, analysed and utilized for finding a suboptimal operating point trajectory. We use a Willan s efficiency model for the engine, expanded with a first order delay dependent torque reduction representing the turbocharger pressure, and study different output power transients. The analysis is made with dynamic programming, Pontryagin’s maximum principle and a suboptimal strategy based on the static optimal operating points. We present a method for using Pontryagin’s maximum principle for deriving the optimal operating point trajectory. The time needed for computation was reduced a factor >100 compared to dynamic programming, but this method is only applicable to load cases with steps between different high output powers. We also present a suboptimal method which shows a <1% increase in fuel consumption compared to the optimal, while reducing the time needed for computation a factor >1000 compared to dynamic programming.

  • 9.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimized Engine Transients2011In: Proceedings of the 7th IEEE vehicle power and propulsion conference, IEEE , 2011, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Recent development has renewed the interest in drivetrain concepts which give a higher degree of freedom by disconnecting the engine and vehicle speeds. This freedom raises the demand for active control, which especially during transients is not trivial but of which the quality is crucial for the success of the drivetrain concept. This work attempts to analyze and explain the fuel optimal solution for the simplest drivetrain setup, which is an engine connected to a load which does not restrict the engine speed. This is made by using a Willan's model for the engine and deriving the fuel optimal solution during output power transients. The analysis is made with dynamic programming, Pontryagin's maximum principle and backward simulation under a static optimal line restriction. The analysis show that the optimal transients can be explained, visualized and, in simple cases, derived from phase planes of the engine speed and the Lagrange multiplier. In these cases the time needed for computation was reduced a factor >; 1000 compared to dynamic programming. Restricting the engine to the static optimal line turns out to be very close to optimal, even during highly transient operation, while reducing the time needed for computation a factor ≫ 1000.

  • 10.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fröberg, Anders
    Volvo Construction Equipment, Sweden.
    Åslund, Jan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Predictive control of a diesel electric wheel loader powertrain2015In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 41, p. 47-56Article in journal (Refereed)
    Abstract [en]

    Wheel loaders often have a highly repetitive pattern of operation, which can be used for creating a rough prediction of future operation. As the present torque converter based transmission is replaced with an infinitely variable device, such as an electric or hydraulic transmission, a freedom in the choice of engine speed is introduced. This choice is far from trivial in the extremely transient operation of these machines, but the availability of a load prediction should be utilized.

    In this paper, a predictive engine and generator controller, based on stochastic dynamic programming, is described, implemented and evaluated. The evaluation is performed against non-predictive controllers in the same system, to lift out any possible benefits of utilizing the repetition based prediction. Simulations and field tests show that the controllers are able to handle disturbances introduced from model errors, the machine environment and the human operator, and that the predictive controller gives around 5% lower fuel consumption than the non-predictive reference controllers.

  • 11.
    Nilsson, Tomas
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Fröberg, Anders
    Volvo Construction Equipment, Eskilstuna, Sweden .
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Using Stochastic Dynamic Programming for look-ahead control of a Wheel Loader Diesel Electric Transmission2014In: IFAC Proceedings Volumes / [ed] Edward Boje, University of Cape Town, South Africa and Xiaohua Xia, University of Pretoria, South Africa, IFAC Papers Online, 2014, Vol. 47, p. 6630-6635Conference paper (Refereed)
    Abstract [en]

    Three Stochastic Dynamic Programming (SDP) implementations are developed for control of a diesel-electric wheel loader transmission. The implementations each use a stochastic description of the load, with the probabilities either independent of the states, dependent on previous power or on distance driven. Both the cycles used for the controller development and for the evaluation are derived from a measured sequence of cycles.

    The evaluation shows that SDP can be used for control of the engine speed and that the resulting trajectories from the three implementations are very similar. The most surprising part is that the method which has constant load probability is able to adjust to the actual load. The combination of the calculation efforts and the outcomes leads to the conclusion that the constant load probability implementation is superior to the other versions.

  • 12.
    Nilsson, Tomas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nyberg, Peter
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Robust Driving Pattern Detection and Identification with a Wheel Loader Application2014In: International journal of vehicle systems modelling and testing, ISSN 1745-6436, Vol. 9, no 1, p. 56-76Article in journal (Refereed)
    Abstract [en]

    Information about wheel loader usage can be used in several ways to optimize customer adaption. First, optimizing the configuration and component sizing of a wheel loader to customer needs can lead to a significant improvement in e.g. fuel efficiency and cost. Second, relevant driving cycles to be used in the development of wheel loaders can be extracted from usage data. Third, on-line usage identification opens up for the possibility of implementing advanced look-ahead control strategies for wheel loader operation. The main objective here is to develop an on-line algorithm that automatically, using production sensors only, can extract information about the usage of a machine. Two main challenges are that sensors are not located with respect to this task and that significant usage disturbances typically occur during operation. The proposed method is based on a combination of several individually simple techniques using signal processing, state automaton techniques, and parameter estimation algorithms. The approach is found to berobust when evaluated on measured data of wheel loaders loading gravel and shot rock.

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