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  • 1.
    Bachmann, Bernhard
    et al.
    Dept. Mathematics and Engineering, University of Applied Sciences, Bielefeld, Germany.
    Ochel, Lennart
    Dept. Mathematics and Engineering, University of Applied Sciences, Bielefeld, Germany.
    Ruge, Vitalij
    Dept. Mathematics and Engineering, University of Applied Sciences, Bielefeld, Germany.
    Gebremedhin, Mahder
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, PELAB - Programming Environment Laboratory.
    Fritzson, Peter
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, PELAB - Programming Environment Laboratory.
    Nezhadali, Vaheed
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Parallel Multiple-Shooting and Collocation Optimization with OpenModelica2012In: Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany, Linköping University Electronic Press, 2012, p. 659-668, article id 067Conference paper (Refereed)
    Abstract [en]

    Nonlinear model predictive control (NMPC) has become increasingly important for today’s control engineers during the last decade. In order to apply NMPC a nonlinear optimal control problem (NOCP) must be solved which needs a high computational effort.

    State-of-the-art solution algorithms are based on multiple shooting or collocation algorithms; which are required to solve the underlying dynamic model formulation. This paper describes a general discretization scheme applied to the dynamic model description which can be further concretized to reproduce the mul-tiple shooting or collocation approach. Furthermore; this approach can be refined to represent a total collocation method in order to solve the underlying NOCP much more efficiently. Further speedup of optimization has been achieved by parallelizing the calculation of model specific parts (e.g. constraints; Jacobians; etc.) and is presented in the coming sections.

    The corresponding discretized optimization problem has been solved by the interior optimizer Ipopt. The proposed parallelized algorithms have been tested on different applications. As industrial relevant application an optimal control of a Diesel-Electric power train has been investigated. The modeling and problem description has been done in Optimica and Modelica. The simulation has been performed using OpenModelica. Speedup curves for parallel execution are presented.

  • 2.
    Ekberg, Kristoffer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering.
    Cycle Beating - An Analysis of the Boundaries During Vehicle Testing2016In: IFAC PAPERS ONLINE, ELSEVIER SCIENCE BV , 2016, Vol. 49, no 11, p. 657-664Conference paper (Refereed)
    Abstract [en]

    Todays vehicle industry is strictly controlled by environmental legislations. The vehicle industry is spending much money out reducing the fuel consumption and fulfilling the emission requirements to make sales possible in different regions in the world. Before introducing; a vehicle on the market, it is tested according to standardized driving cycles to specify the vehicle pollutant emissions and fuel consumption. These cycles allow some deviation from the reference vehicle speed during tests, e.g. NEDC allows deviations of +/- 2 km/h and +/- 1 s. This paper uses dynamic programming to find fuel optimal velocity profiles, given the allowed deviations of +/- 2 km/h and +/- 1 s from reference speed during drive cycle test. By taking advantage of the allowed deviation, the fuel consumption can be reduced by up to 16.56 % according to model results, ruoriing NEDC if gear selections are unrestricted (i.e. using automatic gearbox), and up to 5.90 % if changing gears according to the specifications in the drive cycle. Two different optimization goals are investigated, minimum amount of mass fuel consumed and best mileage. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 3.
    Eriksson, Lars
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Calculation of Optimal Heat Release Rates under Constrained Conditions2016In: SAE International Journal of Engines, ISSN 1946-3936, E-ISSN 1946-3944, Vol. 9, no 2, p. 1143-1162Article in journal (Refereed)
    Abstract [en]

    The work extends a methodology, for searching for optimal heat release profiles, by adding complex constraints on states. To find the optimum heat release profile a methodology, that uses available theory and methods, was developed that enables the use of state of the art optimal control software to find the optimum combustion trace for a model. The methodology is here extended to include constraints and the method is then applied to study how sensitive the solution is to different effects such as heat transfer, crevice flow, maximum rate of pressure rise, maximum pressure, knock and NO generation. The Gatowski single zone model is extended to a pseudo two zone model, to get an unburned zone that is used to describe the knocking and a burned zone for NO generation. A modification of the extended Zeldovich mechanism that makes it continuously differentiable, is used for NO generation. Previous results showed that the crevice effect had a significant influence on the shape for the unconstrained case where a two mode combustion was seen, one initial pressure rise and one constant pressure phase. Here it is shown that it still has a significant influence on the appearance until the maximum pressure limit is reached and becomes the dominating constraint. In the unconstrained case no conditions had combustion before TDC all started after, but when limitations are considered and come into play the combustion can now start before TDC to avoid excessive losses during the expansion. When introducing constraints on the NO formation through the extended Zeldovich mechanism the combustion takes the shape of a three mode combustion, one initial rapid burning, one later rapid burning and a constant pressure phase. In summary it is shown that the methodology is able to cope with the introduced constraints.

  • 4.
    Eriksson, Lars
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Computing Optimal Heat Release Rates in Combustion Engines2015In: SAE International Journal of Engines, ISSN 1946-3936, E-ISSN 1946-3944, Vol. 8, no 2Article in journal (Refereed)
    Abstract [en]

    The combustion process has a high impact on the engine efficiency, and in the search for efficient engines it is of interest to study the combustion. Optimization and optimal control theory is used to compute the most efficient combustion profiles for single zone model with heat transfer and crevice effects. A model is first developed and tuned to experimental data, the model is a modification of the well known Gatowski-model (Gatowski et.al 1984). This model is selected since it gives a very good description of the in-cylinder pressure, and thus the produced work, and achieves this with a low computational complexity. This enables an efficient search method that can maximize the work to be developed. First, smooth combustion profiles are studied where the combustion is modeled using the Vibe function, and parametric optimization is used to search for the optimal profile. Then, the most efficient combustion process with a completely free combustion is studied with theory and software for optimal control. A parameter study is performed to analyze the impact of crevice volume and air/fuel ratio λ. The results show that the losses have a high impact on the behavior, which is natural, and that the crevice effect has a very distinct effect on the optimal combustion giving a two mode appearance similar to the Seiliger cycle.

  • 5.
    Nezhadali, Vaheed
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Turbocharger Dynamics Influence on Optimal Control of Diesel Engine Powered Systems2014In: SAE International Journal of Engines, ISSN 1946-3936, Vol. 7, no 1, p. 6-13Article in journal (Refereed)
    Abstract [en]

    The importance of including turbocharger dynamics in diesel engine models are studied, especially when optimization techniques are to be used to derive the optimal controls. This is done for two applications of diesel engines where in the first application, a diesel engine in wheel loader powertrain interacts with other subsystems to perform a loading operation and engine speed is dictated by the wheel speed, while in the second application, the engine operates in a diesel-electric powertrain as a separate system and the engine speed remains a free variable. In both applications, mean value engine models of different complexities are used while the rest of system components are modeled with the aim of control study. Optimal control problems are formulated, solved, and results are analyzed for various engine loading scenarios in the two applications with and without turbocharger dynamics. It is shown that depending on the engine loading transients, fuel consumption and operation time can widely vary when the turbocharger dynamics are considered in the diesel engine model. Including these, have minor effects on fuel consumption and operation time at minimum fuel operations of the first application (~0.1 %) while the changes are considerable in the second application (up to 60%). In case of minimum time operations however, fuel consumption and operation time are highly affected in both applications implying that not considering turbocharger dynamics in the diesel engine models may lead to overestimation of the engine performance especially when the results are going to be used for control purposes.

  • 6.
    Sciarretta, A.
    et al.
    IFP Energies Nouvelles, France .
    Serrao, L.
    Dana Corporation, Italy.
    Dewangan, P.C.
    IFP Energies Nouvelles, France; IFP School, France .
    Tona, P.
    IFP Energies Nouvelles, France .
    Bergshoeff, E.N. D.
    TU Eindhoven, Netherlands.
    Bordons, C.
    University of Seville, Spain .
    Charmpa, L.
    IFP Sch, France Continental, France .
    Elbert, Ph.
    ETH Zurich, Switzerland.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Hofman, T.
    TU Eindhoven, Netherlands .
    Hubacher, M.
    TU Eindhoven, Netherlands .
    Isenegger, R.
    TU Eindhoven, Netherlands .
    Lacandia, F.
    Ohio State University, USA.
    Laveau, A.
    IFP School, France.
    Li, H.
    IFP School, France.
    Marcos, D.
    University of Seville, Spain .
    Nueesch, T.
    ETH Zurich, Switzerland.
    Onori, S.
    Ohio State University, USA .
    Pisu, P.
    Clemson University, USA .
    Rios, J.
    Clemson University, USA .
    Silvas, E.
    TU Eindhoven, Netherlands .
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Tribioli, L.
    Ohio State University, USA .
    van der Hoeven, A.-J.
    TU Eindhoven, Netherlands .
    Wu, M.
    IFP School, France.
    A control benchmark on the energy management of a plug-in hybrid electric vehicle2014In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 29, p. 287-298Article in journal (Refereed)
    Abstract [en]

    A benchmark control problem was developed for a special session of the IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling (E-COSM 12), held in Rueil-Malmaison, France, in October 2012. The online energy management of a plug-in hybrid-electric vehicle was to be developed by the benchmark participants. The simulator, provided by the benchmark organizers, implements a model of the GM Voltec powertrain. Each solution was evaluated according to several metrics, comprising of energy and fuel economy on two driving profiles unknown to the participants, acceleration and braking performance, computational performance. The nine solutions received are analyzed in terms of the control technique adopted (heuristic rule-based energy management vs. equivalent consumption minimization strategies, ECMS), battery discharge strategy (charge depleting-charge sustaining vs. blended mode), ECMS implementation (vector-based vs. map-based), ways to improve the implementation and improve the computational performance. The solution having achieved the best combined score is compared with a global optimal solution calculated offline using the Pontryagins minimum principle-derived optimization tool HOT.

  • 7.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Adaptive Control Using Map-Based ECMS for a PHEV2012In: E-COSM'12 -- IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, 2012, p. 357-362Conference paper (Refereed)
    Abstract [en]

    A plug-in hybrid electric vehicle(PHEV) is a promising way of achieving the benefits of the electric vehicle without being limited by the electric range. This paper develops an adaptive control strategy based on a map-based ECMS approach. The control is developed andimplemented in a simulator provided by IFP Energies nouvelles for the PHEV benchmark. The implemented control strives to be as blended as possible, whilst still ensuring that all electric energy is used in the driving mission. The controller is adaptive to reduce the importance ofcorrect initial values but since the initial values aect the consumption a method is developed to estimate the optimal initial value for the controller based on driving cycle information. This is seen to work well for most driving cycles with promising consumption results. The controller also fulfills all requirements set by the PHEV Benchmark.

  • 8.
    Sivertsson, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Control of Electrified Powertrains2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Vehicle powertrain electrification, i.e. combining the internal combustion engine (ICE) with an electric motor (EM), is a potential way of meeting the increased demands for efficient and low emission transportation, at a price of increased powertrain complexity since more degrees of freedom (DoF) have been introduced. Optimal control is used in a series of studies of how to best exploit the additional DoFs.

    In a diesel-electric powertrain the absence of a secondary energy storage and mechanical connection between the ICE and the wheels means that all electricity used by the EMs needs to be produced simultaneously by the ICE, whose rotational speed is a DoF. This in combination with the relatively slow dynamics of the turbocharger in the ICE puts high requirements on good transient control. In optimal control studies, accurate models with good extrapolation properties are needed. For this aim two nonlinear physics based models are developed and made available that fulfill these requirements, these are also smooth in the region of interest, to enable gradient based optimization techniques. Using optimal control and one of the developed models, the turbocharger dynamics are shown to have a strong impact on how to control the powertrain and neglecting these can lead to erroneous estimates both in the response of the powertrain as well as how the powertrain should be controlled. Also the objective, whether time or fuel is to be minimized, influences the engine speed-torque path to be used, even though it is shown that the time optimal solution is almost fuel optimal. To increase the freedom of the powertrain control, a small energy storage can be added to assist in the transients. This is shown to be especially useful to decrease the response time of the powertrain, but the manner it is used, depends on the time horizon of the optimal control problem.

    The resulting optimal control solutions are for certain cases oscillatory when stationary controls would have been expected. This is shown to be neither an artifact of the discretization used nor a result of the modeling assumptions used. Instead it is for the formulated problems actually optimal to use periodic control in certain stationary operating points. Measurements show that the pumping torque is different depending on whether the controls are periodic or constant despite the same average value. Whether this is beneficial or not depends on the operating point and control frequency, but can be predicted using optimal periodic control theory.

    In hybrid electric vehicles (HEV) the size of the energy storage reduces the impact of poor transient control, since the battery can compensate for the slower dynamics of the ICE. For HEVs the problem instead is how and when to use the battery to ensure good fuel economy. An adaptive map-based equivalent consumption minimization strategy controller using battery state of charge for feedback control is designed and tested in a real vehicle with good results, even when the controller is started with poor initial values. In a plug-in HEV (PHEV) the battery is even larger, enabling all-electric drive, making it it desirable to use the energy in the battery during the driving mission. A controller is designed and implemented for a PHEV Benchmark and is shown to perform well even for unknown driving cycles, requiring a minimum of future knowledge.

    List of papers
    1. Optimal Transient Control Trajectories in Diesel-Electric Systems-Part I: Modeling, Problem Formulation, and Engine Properties
    Open this publication in new window or tab >>Optimal Transient Control Trajectories in Diesel-Electric Systems-Part I: Modeling, Problem Formulation, and Engine Properties
    2015 (English)In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2, article id 021601Article in journal (Refereed) Published
    Abstract [en]

    A nonlinear four state-three input mean value engine model (MVEM), incorporating the important turbocharger dynamics, is used to study optimal control of a diesel-electric powertrain during transients. The optimization is conducted for the two criteria, minimum time and fuel, where both engine speed and engine power are considered free variables in the optimization. First, steps from idle to a target power are studied and for steps to higher powers the controls for both criteria follow a similar structure, dictated by the maximum torque line and the smoke-limiter. The end operating point, and how it is approached is, however, different. Then, the power transients are extended to driving missions, defined as, that a certain power has to be met as well as a certain energy has to be produced. This is done both with fixed output profiles and with the output power being a free variable. The time optimal control follows the fixed output profile even when the output power is free. These solutions are found to be almost fuel optimal despite being substantially faster than the minimum fuel solution with variable output power. The discussed control strategies are also seen to hold for sequences of power and energy steps.

    Place, publisher, year, edition, pages
    American Society of Mechanical Engineers (ASME), 2015
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-114415 (URN)10.1115/1.4028359 (DOI)000348050800006 ()
    Available from: 2015-03-02 Created: 2015-02-20 Last updated: 2018-01-30
    2. Optimal Transient Control Trajectories in Diesel-Electric Systems-Part II: Generator and Energy Storage Effects
    Open this publication in new window or tab >>Optimal Transient Control Trajectories in Diesel-Electric Systems-Part II: Generator and Energy Storage Effects
    2015 (English)In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2, article id 021602Article in journal (Refereed) Published
    Abstract [en]

    The effects of generator model and energy storage on the optimal control of a diesel-electric powertrain in transient operation are studied. Two different types of problems are solved, minimum fuel and minimum time, with different generator models and limits as well as with an extra energy storage. For this aim, a four-state mean value engine model (MVEM) is used together with models for the generator and energy storage losses. In the optimization both the engines output power and speed are free variables. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. The main characteristics are seen to be independent of generator model and limits; they, however, shift the peak efficiency regions and therefore the stationary points. For minimum fuel transients, the energy storage remains virtually unused for all requested energies, for minimum time it is used to reduce the response time. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time. The possibility to reduce the response time is seen to hold for a large range of values of energy storage parameters. The minimum fuel solutions remain unaffected when changing the energy storage parameters, implying it is not beneficial to use an energy storage if fuel consumption is to be minimized. Close to the minimum time solution, the fuel consumption with low required energy is quite sensitive to variations in duration, for larger energies it is not. Near the minimum fuel solution changes in duration have only minor effects on the fuel consumption.

    Place, publisher, year, edition, pages
    American Society of Mechanical Engineers (ASME), 2015
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-114416 (URN)10.1115/1.4028360 (DOI)000348050800007 ()
    Available from: 2015-03-02 Created: 2015-02-20 Last updated: 2018-01-30
    3. Turbocharger Dynamics Influence on Optimal Control of Diesel Engine Powered Systems
    Open this publication in new window or tab >>Turbocharger Dynamics Influence on Optimal Control of Diesel Engine Powered Systems
    2014 (English)In: SAE International Journal of Engines, ISSN 1946-3936, Vol. 7, no 1, p. 6-13Article in journal (Refereed) Published
    Abstract [en]

    The importance of including turbocharger dynamics in diesel engine models are studied, especially when optimization techniques are to be used to derive the optimal controls. This is done for two applications of diesel engines where in the first application, a diesel engine in wheel loader powertrain interacts with other subsystems to perform a loading operation and engine speed is dictated by the wheel speed, while in the second application, the engine operates in a diesel-electric powertrain as a separate system and the engine speed remains a free variable. In both applications, mean value engine models of different complexities are used while the rest of system components are modeled with the aim of control study. Optimal control problems are formulated, solved, and results are analyzed for various engine loading scenarios in the two applications with and without turbocharger dynamics. It is shown that depending on the engine loading transients, fuel consumption and operation time can widely vary when the turbocharger dynamics are considered in the diesel engine model. Including these, have minor effects on fuel consumption and operation time at minimum fuel operations of the first application (~0.1 %) while the changes are considerable in the second application (up to 60%). In case of minimum time operations however, fuel consumption and operation time are highly affected in both applications implying that not considering turbocharger dynamics in the diesel engine models may lead to overestimation of the engine performance especially when the results are going to be used for control purposes.

    Place, publisher, year, edition, pages
    SAE International, 2014
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117316 (URN)10.4271/2014-01-0290 (DOI)
    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-01-30
    4. Optimal and real-time control potential of a diesel-electric powertrain
    Open this publication in new window or tab >>Optimal and real-time control potential of a diesel-electric powertrain
    2014 (English)In: Proceedings of the 19th World CongressThe International Federation of Automatic ControlCape Town, South Africa. August 24-29, 2014 / [ed] Edward Boje and Xiaohua Xia, Cape Town: International Federation of Automatic Control , 2014, Vol. 19, p. 4825-4830Conference paper, Published paper (Refereed)
    Abstract [en]

    Real-time control strategies and their performance related to the optimal control trajectories for a diesel-electric powertrain in transient operation are studied. The considered transients are steps from idle to target power. A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics, is used for this study. The strategies are implemented using the SAE J1939-standard for engine control and evaluated compared to both the optimal solution and the solution when the engine is restricted to follow its stationary optimal line. It is shown that with the control parameters tuned for a specific criteria both engine control strategies in the SAE J1939-standard, speed control and load control, can achieve almost optimal results, where engine load controlled shows a better trade-off between fuel economy and duration. The controllers are then extended and it is shown that it is possible to control the powertrain in a close to optimal way using the SAE J1939-standard, both with the engine speed and load controlled. However the mode where the engine is load controlled is seen to be more robust.

    Place, publisher, year, edition, pages
    Cape Town: International Federation of Automatic Control, 2014
    Series
    World Congress, ISSN 1474-6670 ; Volume 19, Part 1
    Keywords
    Nonlinear and optimal automotive control; Control architectures in automotive control; Engine modelling and control
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117333 (URN)10.3182/20140824-6-ZA-1003.01969 (DOI)978-3-902823-62-5 (ISBN)
    Conference
    The 19th World Congress The International Federation of Automatic Control Cape Town, South Africa. August 24-29, 2014
    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-01-30Bibliographically approved
    5. Modeling for Optimal Control: A Validated Diesel-Electric Powertrain Model
    Open this publication in new window or tab >>Modeling for Optimal Control: A Validated Diesel-Electric Powertrain Model
    2014 (English)In: Proceedings of the 55th Conference on Simulation and Modelling (SIMS 55), Modelling, Simulation and Optimization, 21-22 October 2014, Aalborg, Denmark / [ed] Alireza Rezania Kolai, Kim Sørensen & Mads Pagh Nielsen, Linköping: Linköping University Electronic Press, 2014, p. 49-58Conference paper, Published paper (Refereed)
    Abstract [en]

    An optimal control ready model of a diesel-electric powertrain is developed,validated and provided to the research community. The aim ofthe model is to facilitate studies of the transient control of diesel-electricpowertrains and also to provide a model for developers of optimizationtools. The resulting model is a four state three control mean valueengine model that captures the significant nonlinearity of the diesel engine, while still being continuously differentiable.

    Place, publisher, year, edition, pages
    Linköping: Linköping University Electronic Press, 2014
    Series
    Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 108
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117334 (URN)978-91-7519-376-2 (ISBN)
    Conference
    SIMS 2014 - 55th International Conference on Simulation and Modelling
    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-02-15Bibliographically approved
    6. An Optimal Control Benchmark: Transient Optimization of a Diesel-Electric Powertrain
    Open this publication in new window or tab >>An Optimal Control Benchmark: Transient Optimization of a Diesel-Electric Powertrain
    2014 (English)In: Proceedings of the 55th International Conference on Simulation and Modelling (SIMS 55), 21-22 October, Modelling, Simulation and Optimization / [ed] Alireza Rezania Kolai, Kim Sørensen & Mads Pagh Nielsen, Linköping University Electronic Press, 2014, p. 59-63Conference paper, Published paper (Refereed)
    Abstract [en]

    An optimal control benchmark is presented and discussed. The benchmark is optimal transient control of a nonlinear four state three control model of a diesel-electric powertrain and constructed in such a manner that it is available in several versions to be of interest for developers of optimal control tools at different levels of development. This includes with and without time as a parameter as well as with and without time varying constraints.

    Place, publisher, year, edition, pages
    Linköping University Electronic Press, 2014
    Series
    Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 108
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117335 (URN)978-91-7519-376-2 (ISBN)
    Conference
    SIMS 2014 - 55th International Conference on Simulation and Modelling, October 21-22, Aalborg, Denmark
    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-02-20Bibliographically approved
    7. Model and discretization impact on oscillatory optimal control for a diesel-electric powertrain
    Open this publication in new window or tab >>Model and discretization impact on oscillatory optimal control for a diesel-electric powertrain
    2015 (English)In: 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM 2015 Columbus, Ohio, USA, 23-26 August 2015, Elsevier, 2015, Vol. 48(15), p. 66-71Conference paper, Published paper (Refereed)
    Abstract [en]

    A mean value engine model is used to study optimal control of a diesel-electric powertrain. The resulting optimal controls are shown to be highly oscillating for certain operating points, raising the question whether this is an artifact of discretization, modeling choices or a phenomenon available in real engines. Several model extensions are investigated and their corresponding optimal control trajectories are studied. It is shown that the oscillating controls cannot be explained by the implemented extensions to the previously published model, nor by the discretization, showing that for certain operating points the optimal solution is periodic.

    Place, publisher, year, edition, pages
    Elsevier, 2015
    Series
    IFAC-PapersOnLine, ISSN 2405-8963
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117336 (URN)10.1016/j.ifacol.2015.10.010 (DOI)
    Conference
    4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM 2015 Columbus, Ohio, USA, 23-26 August 2015
    Note

    At the time for thesis presentation publication was in status: Manuscript

    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-01-30Bibliographically approved
    8. Optimal stationary control of diesel engines using periodic control
    Open this publication in new window or tab >>Optimal stationary control of diesel engines using periodic control
    2017 (English)In: Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, ISSN 0954-4070, E-ISSN 2041-2991, Vol. 231, no 4, p. 457-475Article in journal (Refereed) Published
    Abstract [en]

    Measurements and optimal control are used to study whether the fuel economy of a diesel engine can be improved through periodic control of the wastegate, illustrating how modern optimal control tools can be used to identify non-trivial solutions that can improve performance. The measurements show that the pumping torque of the engine is changed when the wastegate is controlled in a periodic manner versus stationary even if the mean position is the same. If this decreases the fuel consumption or not is seen to be frequency and operating point dependent. The measurements indicate that the phenomenon occurs in the time scales capturable by mean value engine models (MVEM). The operating points are further analyzed using a MVEM and optimal control. It is shown that whether the optimal solution exhibits periodic oscillations or not is operating point dependent, but is not due to the instantaneous nature of the controls. Even if an actuator model is added the oscillations persist for reasonable time constants, the frequency of the oscillations is however affected. Further it is shown that the periodic control can be predicted by optimal periodic control theory and that the frequency of the control affects the resulting efficiency.

    Place, publisher, year, edition, pages
    Sage Publications, 2017
    Keywords
    Optimal periodic control, diesel engines, optimal control, internal combustion engines, wastegate control
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-117337 (URN)10.1177/0954407016640631 (DOI)000397211700002 ()2-s2.0-85014504643 (Scopus ID)
    Note

    At the time for thesis presentation publication was in status: Manuscript

    Available from: 2015-04-23 Created: 2015-04-23 Last updated: 2018-01-30Bibliographically approved
    9. Adaptive Control of a Hybrid Powertrain with Map-based ECMS
    Open this publication in new window or tab >>Adaptive Control of a Hybrid Powertrain with Map-based ECMS
    2011 (English)In: Proceedings of the 18th IFAC World Congress, 2011 / [ed] Sergio Bittanti, Angelo Cenedese, Sandro Zampieri, 2011, p. 2949-2954Conference paper, Published paper (Refereed)
    Abstract [en]

    To fully utilize the fuel reduction potential of a hybrid powertrain requires a careful design of the energy management control algorithms. Here a controller is created using mapbased equivalent consumption minimization strategy and implemented to function without any knowledge of the future driving mission. The optimal torque distribution is calculated oine and stored in tables. Despite only considering stationary operating conditions and average battery parameters, the result is close to that of deterministic dynamic programming. Eects of making the discretization of the tables sparser are also studied and found to have only minor eects on the fuel consumption. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear that would give the lowest consumption. Two ways of adapting the control according to the battery state of charge are proposed and investigated. One of the adaptive strategies is experimentally evaluated and found to ensure charge sustenance despite poor initial values.

    Series
    World Congress, ISSN 1474-6670 ; Volume 18, Part 1
    Keywords
    Hybrid Vehicles, Adaptive Control, Automotive Control, Optimal Control
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-84957 (URN)10.3182/20110828-6-IT-1002.02091 (DOI)978-390266193-7 (ISBN)
    Conference
    18th IFAC World Congress; August 28-September 2, Milano; Italy
    Available from: 2012-10-29 Created: 2012-10-29 Last updated: 2018-01-30Bibliographically approved
    10. A control benchmark on the energy management of a plug-in hybrid electric vehicle
    Open this publication in new window or tab >>A control benchmark on the energy management of a plug-in hybrid electric vehicle
    Show others...
    2014 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 29, p. 287-298Article in journal (Refereed) Published
    Abstract [en]

    A benchmark control problem was developed for a special session of the IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling (E-COSM 12), held in Rueil-Malmaison, France, in October 2012. The online energy management of a plug-in hybrid-electric vehicle was to be developed by the benchmark participants. The simulator, provided by the benchmark organizers, implements a model of the GM Voltec powertrain. Each solution was evaluated according to several metrics, comprising of energy and fuel economy on two driving profiles unknown to the participants, acceleration and braking performance, computational performance. The nine solutions received are analyzed in terms of the control technique adopted (heuristic rule-based energy management vs. equivalent consumption minimization strategies, ECMS), battery discharge strategy (charge depleting-charge sustaining vs. blended mode), ECMS implementation (vector-based vs. map-based), ways to improve the implementation and improve the computational performance. The solution having achieved the best combined score is compared with a global optimal solution calculated offline using the Pontryagins minimum principle-derived optimization tool HOT.

    Place, publisher, year, edition, pages
    Pergamon Press, 2014
    Keywords
    Supervisory control; Plug-in hybrid electric vehicles; Energy management; Optimal control; Rule-based control
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-109361 (URN)10.1016/j.conengprac.2013.11.020 (DOI)000339133700026 ()
    Available from: 2014-08-15 Created: 2014-08-15 Last updated: 2018-01-30Bibliographically approved
    11. Design and Evaluation of Energy Management using Map-Based ECMS for the PHEV Benchmark
    Open this publication in new window or tab >>Design and Evaluation of Energy Management using Map-Based ECMS for the PHEV Benchmark
    2014 (English)In: Oil & gas science and technology, ISSN 1294-4475, E-ISSN 1953-8189, Vol. 70, no 1, p. 195-211Article in journal (Refereed) Published
    Abstract [en]

    Plug-in Hybrid Electric Vehicles (PHEV) provide a promising way of achieving the benefits of the electric vehicle without being limited by the electric range, but they increase the importance of the supervisory control to fully utilize the potential of the powertrain. The winning contribution in the PHEV Benchmark organized by IFP Energies nouvelles is described and evaluated. The control is an adaptive strategy based on a map-based Equivalent Consumption Minimization Strategy (ECMS) approach, developed and implemented in the simulator provided for the PHEV Benchmark. The implemented control strives to be as blended as possible, whilst still ensuring that all electric energy is used in the driving mission. The controller is adaptive to reduce the importance of correct initial values, but since the initial values affect the consumption, a method is developed to estimate the optimal initial value for the controller based on driving cycle information. This works well for most driving cycles with promising consumption results. The controller performs well in the benchmark; however, the driving cycles used show potential for improvement. A robustness built into the controller affects the consumption more than necessary, and in the case of altitude variations the control does not make use of all the energy available. The control is therefore extended to also make use of topography information that could be provided by a GPS which shows a potential further decrease in fuel consumption.

    Place, publisher, year, edition, pages
    Institut Francais du Petrole, 2014
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-117268 (URN)10.2516/ogst/2014018 (DOI)000351444400013 ()
    Available from: 2015-04-22 Created: 2015-04-21 Last updated: 2018-01-30
  • 9.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    An Optimal Control Benchmark: Transient Optimization of a Diesel-Electric Powertrain2014In: Proceedings of the 55th International Conference on Simulation and Modelling (SIMS 55), 21-22 October, Modelling, Simulation and Optimization / [ed] Alireza Rezania Kolai, Kim Sørensen & Mads Pagh Nielsen, Linköping University Electronic Press, 2014, p. 59-63Conference paper (Refereed)
    Abstract [en]

    An optimal control benchmark is presented and discussed. The benchmark is optimal transient control of a nonlinear four state three control model of a diesel-electric powertrain and constructed in such a manner that it is available in several versions to be of interest for developers of optimal control tools at different levels of development. This includes with and without time as a parameter as well as with and without time varying constraints.

  • 10.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Design and Evaluation of Energy Management using Map-Based ECMS for the PHEV Benchmark2014In: Oil & gas science and technology, ISSN 1294-4475, E-ISSN 1953-8189, Vol. 70, no 1, p. 195-211Article in journal (Refereed)
    Abstract [en]

    Plug-in Hybrid Electric Vehicles (PHEV) provide a promising way of achieving the benefits of the electric vehicle without being limited by the electric range, but they increase the importance of the supervisory control to fully utilize the potential of the powertrain. The winning contribution in the PHEV Benchmark organized by IFP Energies nouvelles is described and evaluated. The control is an adaptive strategy based on a map-based Equivalent Consumption Minimization Strategy (ECMS) approach, developed and implemented in the simulator provided for the PHEV Benchmark. The implemented control strives to be as blended as possible, whilst still ensuring that all electric energy is used in the driving mission. The controller is adaptive to reduce the importance of correct initial values, but since the initial values affect the consumption, a method is developed to estimate the optimal initial value for the controller based on driving cycle information. This works well for most driving cycles with promising consumption results. The controller performs well in the benchmark; however, the driving cycles used show potential for improvement. A robustness built into the controller affects the consumption more than necessary, and in the case of altitude variations the control does not make use of all the energy available. The control is therefore extended to also make use of topography information that could be provided by a GPS which shows a potential further decrease in fuel consumption.

  • 11.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Generator Effects on the Optimal Control of a Power Assisted Diesel-Electric Powertrain2013In: IEEE VPPC 2013 – The 9th IEEE Vehicle Power and Propulsion Conference, Institute of Electrical and Electronics Engineers (IEEE), 2013Conference paper (Refereed)
    Abstract [en]

    Optimal control of a diesel-electric powertrain in transient operation is studied. The attention is on how generator limits affect the solution, as well as how the addition of a small energy storage can assist in the transients. Two different types of problems are solved, minimum fuel and minimum time, with different generator limits as well as with and without an extra energy storage. In the optimization both the output power and engine speed are free variables. For this aim a 4-state mean value engine model is used together with models for the generator and energy storage losses. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. For minimum fuel transients the energy storage remains virtually unused for all requested energies, for minimum time it does not. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time.

  • 12.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Model and discretization impact on oscillatory optimal control for a diesel-electric powertrain2015In: 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling E-COSM 2015 Columbus, Ohio, USA, 23-26 August 2015, Elsevier, 2015, Vol. 48(15), p. 66-71Conference paper (Refereed)
    Abstract [en]

    A mean value engine model is used to study optimal control of a diesel-electric powertrain. The resulting optimal controls are shown to be highly oscillating for certain operating points, raising the question whether this is an artifact of discretization, modeling choices or a phenomenon available in real engines. Several model extensions are investigated and their corresponding optimal control trajectories are studied. It is shown that the oscillating controls cannot be explained by the implemented extensions to the previously published model, nor by the discretization, showing that for certain operating points the optimal solution is periodic.

  • 13.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Modeling for Optimal Control: A Validated Diesel-Electric Powertrain Model2014In: Proceedings of the 55th Conference on Simulation and Modelling (SIMS 55), Modelling, Simulation and Optimization, 21-22 October 2014, Aalborg, Denmark / [ed] Alireza Rezania Kolai, Kim Sørensen & Mads Pagh Nielsen, Linköping: Linköping University Electronic Press, 2014, p. 49-58Conference paper (Refereed)
    Abstract [en]

    An optimal control ready model of a diesel-electric powertrain is developed,validated and provided to the research community. The aim ofthe model is to facilitate studies of the transient control of diesel-electricpowertrains and also to provide a model for developers of optimizationtools. The resulting model is a four state three control mean valueengine model that captures the significant nonlinearity of the diesel engine, while still being continuously differentiable.

  • 14.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal and real-time control potential of a diesel-electric powertrain2014In: Proceedings of the 19th World CongressThe International Federation of Automatic ControlCape Town, South Africa. August 24-29, 2014 / [ed] Edward Boje and Xiaohua Xia, Cape Town: International Federation of Automatic Control , 2014, Vol. 19, p. 4825-4830Conference paper (Refereed)
    Abstract [en]

    Real-time control strategies and their performance related to the optimal control trajectories for a diesel-electric powertrain in transient operation are studied. The considered transients are steps from idle to target power. A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics, is used for this study. The strategies are implemented using the SAE J1939-standard for engine control and evaluated compared to both the optimal solution and the solution when the engine is restricted to follow its stationary optimal line. It is shown that with the control parameters tuned for a specific criteria both engine control strategies in the SAE J1939-standard, speed control and load control, can achieve almost optimal results, where engine load controlled shows a better trade-off between fuel economy and duration. The controllers are then extended and it is shown that it is possible to control the powertrain in a close to optimal way using the SAE J1939-standard, both with the engine speed and load controlled. However the mode where the engine is load controlled is seen to be more robust.

  • 15.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Optimal Powertrain Lock-Up Transients for a Heavy Duty Series Hybrid Electric Vehicle2017In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2017, Vol. 50, no 1, p. 7842-7848Conference paper (Refereed)
    Abstract [en]

    Fuel optimal lock-up transients for a heavy duty series hybrid electric vehicle are studied. A mean value engine model is used together with numerical optimal control to investigate the interplay between electric machine, gearbox and engine with its turbocharger dynamics in particular how they influence the manner and rate at which the engine should be controlled in order to reach a synchronized speed with the gear-box, enabling lock-up. This is studied both for prescribed gear-box speeds, simulating a mechanical transmission, and with gear-box speed an optimization variable, simulating a continuously variable transmission. The optimal engine transients and their duration are seen to be dictated by the stationary efficiency of the different drivetrain modes, showing that the ratio between the efficiencies of the electric and mechanical path dominates the dynamics and have a greater effect than the engine and turbocharger dynamics. In particular the transition between the modes is as fast as possible when the conventional powertrain is the most efficient and as slow as possible when the engine-generator set is more efficient. This points out that the stationary efficiency maps can be used in a central way for the control design of lock-up transients. (c) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 16.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Short Driving Mission Control for a Diesel-Electric Powertrain2012In: IEEE VPPC 2012 -- The 8th IEEE Vehicle Power and Propulsion Conference, IEEE , 2012, p. 413-418Conference paper (Refereed)
    Abstract [en]

    Time and fuel optimal control for a diesel-electric powertrain in transient operation is studied using a four state, three controls non-linear mean value engine model. In the studied transients the engine starts at idle and stops when the generated energy fulfills the driving mission requirement. During the driving mission both the engine speed and output power are allowed to vary, but with a constraint on power. Two strategiesare then developed and evaluated. One where the driving mission is optimized with the generator power considered a free variable,and a second strategy where the accelerating phase of the transient is first optimized and then the optimal controls fora fixed generator power are used. The time optimal control is shown to be almost as fuel efficient as the fuel optimal controleven though the gain in time is large. The time optimal control also has the advantage of using constant power output, making itsimple and easily implementable, whilst the fuel optimal control is more complex and changes with the length of the driving mission.

  • 17.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal stationary control of diesel engines using periodic control2017In: Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, ISSN 0954-4070, E-ISSN 2041-2991, Vol. 231, no 4, p. 457-475Article in journal (Refereed)
    Abstract [en]

    Measurements and optimal control are used to study whether the fuel economy of a diesel engine can be improved through periodic control of the wastegate, illustrating how modern optimal control tools can be used to identify non-trivial solutions that can improve performance. The measurements show that the pumping torque of the engine is changed when the wastegate is controlled in a periodic manner versus stationary even if the mean position is the same. If this decreases the fuel consumption or not is seen to be frequency and operating point dependent. The measurements indicate that the phenomenon occurs in the time scales capturable by mean value engine models (MVEM). The operating points are further analyzed using a MVEM and optimal control. It is shown that whether the optimal solution exhibits periodic oscillations or not is operating point dependent, but is not due to the instantaneous nature of the controls. Even if an actuator model is added the oscillations persist for reasonable time constants, the frequency of the oscillations is however affected. Further it is shown that the periodic control can be predicted by optimal periodic control theory and that the frequency of the control affects the resulting efficiency.

  • 18.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Step Responses in Diesel-Electric Systems2012In: Mechatronics'12 -- The 13th Mechatronics Forum International Conference, 2012Conference paper (Refereed)
    Abstract [en]

    A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics,is used to study optimal control of a diesel-electric powertrain during transients. The optimization is conducted for two differentcriteria, both time and fuel optimal control, and both engine speed and output power are considered free variables in theoptimization. The transients considered are steps from idle to a target power and the results of the optimization show thatthe solutions can be divided into two categories, depending on requested power. The resulting control strategies are also seento be valid for other initial conditions than idle. For steps to high power the controls for both criteria follow a similarstructure, a structure given by the maximum torque line and the smoke-limiter. The main difference between fuel and timeoptimal control is the end operating point, and how this is approached. The fuel optimal control builds more kinetic energyin the turbocharger, reducing the necessary amount of kinetic energy in the system to produce the requested power. It is foundthat the fact that it does not approach the fuel optimal operating point relates to the amount of produced energy required to getthere. For steps to low output powers the optimal controls deal with the turbocharger dynamics in a fundamentally differentway.

  • 19.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal transient control and effects of a small energy storage for a diesel-electric powertrain2013In: 7th IFAC Symposium on Advances in Automotive Control, 2013 / [ed] Taketoshi Kawabe, International Federation of Automatic Control , 2013, p. 818-823Conference paper (Refereed)
    Abstract [en]

    Optimal control of a diesel-electric powertrain in transient operation is studied. The attention is on how generator limits affect the solution, as well as how the addition of a small energy storage can assist in the transients. Two different types of problems are solved, minimum fuel and minimum time, with different generator limits as well as with and without an extra energy storage. In the optimization both the output power and engine speed are free variables. For this aim a 4-state mean value engine model is used together with models for the generator and energy storage losses. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. For minimum fuel transients the energy storage remains virtually unused for all requested energies, for minimum time it does not. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time.

  • 20.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Optimal Transient Control Trajectories in Diesel-Electric Systems-Part 1: Modeling, Problem Formulation and Engine Properties2015In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2Article in journal (Refereed)
    Abstract [en]

    A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics, is used to study optimal control of a diesel-electric powertrain during transients. The optimization is conducted for the two criteria, minimum time and fuel, where both engine speed and engine power are considered free variables in the optimization. First, steps from idle to a target power are studied and for steps to higher powers the controls for both criteria follow a similar structure, dictated by the maximum torque line and the smoke-limiter. The end operating point, and how it is approached, is however different. Then the power transients are extended to driving missions, defined as, that a certain power has to be met as well as a certain energy has to be produced. This is done with both fixed output profiles and with the output power being a free variable. The time optimal control follows the fixed output profile even when the output power is free. These solutions are found to be almost fuel optimal despite being substantially faster than the minimum fuel solution with variable output power. The discussed control strategies are also seen to hold for sequences of power and energy steps.

  • 21.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Optimal Transient Control Trajectories in Diesel-Electric Systems-Part 2: Generator and Energy Storage Effects2015In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2Article in journal (Refereed)
    Abstract [en]

    The effects of generator model and energy storage on the optimal control of a diesel-electric powertrain in transient operation is studied. Two different types of problems are solved, minimum fuel and minimum time, with different generator models and limits as well as with an extra energy storage. For this aim a 4-state mean value engine model is used together with models for the generator and energy storage losses. In the optimization both the engines output power and speed are free variables. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. The main characteristics are seen to be independent of generator model and limits, they however shift the peak efficiency regions and therefore the stationary points. For minimum fuel transients the energy storage remains virtually unused for all requested energies, for minimum time it is used to reduce the response time. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time. The possibility to reduce the response time is seen to hold for a large range of values of energy storage parameters. The minimum fuel solutions remain unaffected when changing the energy storage parameters, implying it is not beneficial to use an energy storage if fuel consumption is to be minimized. Close to the minimum time solution the fuel consumption with low required energy is quite sensitive to variations in duration, for larger energies it is not. Near the minimum fuel solution changes in duration have only minor effects on the fuel consumption.

  • 22.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Transient Control Trajectories in Diesel-Electric Systems-Part I: Modeling, Problem Formulation, and Engine Properties2015In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2, article id 021601Article in journal (Refereed)
    Abstract [en]

    A nonlinear four state-three input mean value engine model (MVEM), incorporating the important turbocharger dynamics, is used to study optimal control of a diesel-electric powertrain during transients. The optimization is conducted for the two criteria, minimum time and fuel, where both engine speed and engine power are considered free variables in the optimization. First, steps from idle to a target power are studied and for steps to higher powers the controls for both criteria follow a similar structure, dictated by the maximum torque line and the smoke-limiter. The end operating point, and how it is approached is, however, different. Then, the power transients are extended to driving missions, defined as, that a certain power has to be met as well as a certain energy has to be produced. This is done both with fixed output profiles and with the output power being a free variable. The time optimal control follows the fixed output profile even when the output power is free. These solutions are found to be almost fuel optimal despite being substantially faster than the minimum fuel solution with variable output power. The discussed control strategies are also seen to hold for sequences of power and energy steps.

  • 23.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Optimal Transient Control Trajectories in Diesel-Electric Systems-Part II: Generator and Energy Storage Effects2015In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 137, no 2, article id 021602Article in journal (Refereed)
    Abstract [en]

    The effects of generator model and energy storage on the optimal control of a diesel-electric powertrain in transient operation are studied. Two different types of problems are solved, minimum fuel and minimum time, with different generator models and limits as well as with an extra energy storage. For this aim, a four-state mean value engine model (MVEM) is used together with models for the generator and energy storage losses. In the optimization both the engines output power and speed are free variables. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. The main characteristics are seen to be independent of generator model and limits; they, however, shift the peak efficiency regions and therefore the stationary points. For minimum fuel transients, the energy storage remains virtually unused for all requested energies, for minimum time it is used to reduce the response time. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time. The possibility to reduce the response time is seen to hold for a large range of values of energy storage parameters. The minimum fuel solutions remain unaffected when changing the energy storage parameters, implying it is not beneficial to use an energy storage if fuel consumption is to be minimized. Close to the minimum time solution, the fuel consumption with low required energy is quite sensitive to variations in duration, for larger energies it is not. Near the minimum fuel solution changes in duration have only minor effects on the fuel consumption.

  • 24.
    Sivertsson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Time and Fuel Optimal Power Response of a Diesel-Electric Powertrain2012In: E-COSM'12 -- IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, 2012, p. 262-269Conference paper (Refereed)
    Abstract [en]

    Optimal control policies for a diesel-electric powertrain in transient operation are studied. In order to fully utilize the extra degree of freedom available in a diesel-electric powertrain, compared to a conventional powertrain, the engine-speed is allowed to vary freely.The considered transients are steps from idle to target power. A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics, is used for this study. The study is conducted for two dierent criteria, fuel optimal control and time optimalcontrol. The results from the optimization show that the optimal controls for each criteria can be divided into two categories, one for high requested powers and one for low requested powers. For high power transients the controls for both criteria follow a similar structure, a structure givenby the maximum torque line and the smoke-limiter. The main dierence between the criteria is the end point and how it is approached. The fuel optimal control builds more kinetic energy in the turbocharger, reducing the necessary amount of kinetic energy in the system to producethe requested power. For low power transients the optimal controls deal with the turbocharger dynamics in a fundamentally dierent way.

  • 25.
    Sivertsson, Martin
    et al.
    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.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Adaptive Control of a Hybrid Powertrain with Map-based ECMS2011In: Proceedings of the 18th IFAC World Congress, 2011 / [ed] Sergio Bittanti, Angelo Cenedese, Sandro Zampieri, 2011, p. 2949-2954Conference paper (Refereed)
    Abstract [en]

    To fully utilize the fuel reduction potential of a hybrid powertrain requires a careful design of the energy management control algorithms. Here a controller is created using mapbased equivalent consumption minimization strategy and implemented to function without any knowledge of the future driving mission. The optimal torque distribution is calculated oine and stored in tables. Despite only considering stationary operating conditions and average battery parameters, the result is close to that of deterministic dynamic programming. Eects of making the discretization of the tables sparser are also studied and found to have only minor eects on the fuel consumption. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear that would give the lowest consumption. Two ways of adapting the control according to the battery state of charge are proposed and investigated. One of the adaptive strategies is experimentally evaluated and found to ensure charge sustenance despite poor initial values.

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