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  • 1.
    Eriksson, Daniel
    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.
    Sequential Residual Generator Selection for Fault Detection2014In: 2014 EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2014, p. 932-937Conference paper (Refereed)
    Abstract [en]

    Structural methods in model-based fault diagnosis applications are simple and efficient tools for finding candidates for residual generation. However, the structural methods do not take model uncertainties and information about fault behavior into consideration. This may result in selecting residual generators with bad performance to be included in the diagnosis system. By using the Kullback-Leibler divergence, the performance of different residual generators can be compared to find the best one. With the ability to quantify diagnostic performance, the design of residual generators can be optimized by, for example, combining several residual generators such that the diagnostic performance is maximized. The proposed method for residual generation selection is applied to a water tank system to show that the achieved residual performance is improved compared to only use a structural method.

  • 2.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault Detection and Isolation2019In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 27, no 2, p. 616-630Article in journal (Refereed)
    Abstract [en]

    Selecting residual generators for detecting and isolating faults in a system is an important step when designing model-based diagnosis systems. However, finding a suitable set of residual generators to fulfill performance requirements is complicated by model uncertainties and measurement noise that have negative impact on fault detection performance. The main contribution is an algorithm for residual selection that combines model-based and data-driven methods to find a set of residual generators that maximizes fault detection and isolation performance. Based on the solution from the residual selection algorithm, a generalized diagnosis system design is proposed where test quantities are designed using multivariate residual information to improve detection performance. To illustrate the usefulness of the proposed residual selection algorithm, it is applied to find a set of residual generators to monitor the air path through an internal combustion engine.

  • 3.
    Llamas, Xavier
    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.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Fuel Efficient Speed Profiles for Finite Time Gear Shift with Multi-Phase Optimization2013In: 54th SIMS Conference on Simulation and Modelling, SIMS 2013, 2013Conference paper (Refereed)
    Abstract [en]

    A method that finds fuel optimal speed profiles for traveling a predefined distance is presented. The vehicle is modeled using a quasistatic formulation and an optimal control problem is defined. In addition, the solving method is based on a multi-phase optimization algorithm based on dynamic programming. This approach results in lower computational time than solving the problem directly with dynamic programming, it also makes the computational time independent of the travel distance. In addition, the simulation generated data can be used to get the solution to several optimal control problems in parallel that have additional constraints. Further a finite time gear shift model is presented to include the gear selection in the optimization problem. The problem also considers speed losses and fuel consumption during the maneuver. The results presented show the optimal speed and gear profiles to cover a distance, making special emphasis at the acceleration phase, where it is optimal to perform a fast acceleration to engage the highest gear as soon as possible. Finally a proposed application is to use the simulation data to provide eco-driving tips to the driver.

  • 4.
    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.

  • 5.
    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.

  • 6.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Model Based Vehicle Level Diagnosis for Hybrid Electric Vehicles2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    When hybridizing a vehicle, new components are added that need to be monitored due to safety and legislative demands. Diagnostic aspects due to powertrain hybridization are investigated, such as that there are more mode switches in the hybrid powertrain compared to a conventional powertrain, and that there is a freedom in choosing operating points of the components in the powertrain via the overall energy management and still fulfill the driver torque request. A model of a long haulage truck is developed, and a contribution is a new electric machine model. The machine model is of low complexity, and treats the machine constants in a different way compared to a standard model. It is shown that this model describes the power losses significantly better when adopted to real data, and that this modeling improvement leads to better signal separation between the non-faulty and faulty cases compared to the standard model.

    To investigate the influence of the energy management design and sensor configuration on the diagnostic performance, two vehicle level diagnosis systems based on different sensor configurations are designed and implemented. It is found that there is a connection between the operating modes of the vehicle and the diagnostic performance, and that this interplay is of special relevance in the system based on few sensors.

    In consistency based diagnosis it is investigated if there exists a solution to a set of equations with analytical redundancy, i.e. there are more equations than unknown variables. The selection of sets of equations to be included in the diagnosis system and in what order to compute the unknown variables in the used equations affect the diagnostic performance. A systematic method that finds properties and constructs residual generator candidates based on a model has been developed. Methods are also devised for utilization of the residual generators, such as initialization of dynamic residual generators, and for consideration of the fault excitation in the residuals using the internal form of the residual generators. For demonstration, the model of the hybridized truck is used in a simulation study, and it is shown that the methods significantly increase the diagnostic performance.

    The models used in a diagnosis system need to be accurate for fault detection. Map based models describe the fault free behavior accurately, but fault isolability is often difficult to achieve using this kind of model. To achieve also good fault isolability performance without extensive modeling, a new diagnostic approach is presented. A map based model describes the nominal behavior, and another model, that is less accurate but in which the faults are explicitly included, is used to model how the faults affect the output signals. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid vehicle, and simulations show that the approach works well.

    List of papers
    1. Overall Monitoring and Diagnosis for Hybrid Vehicle Powertrains
    Open this publication in new window or tab >>Overall Monitoring and Diagnosis for Hybrid Vehicle Powertrains
    2010 (English)In: Proceedings of the 6th IFAC Symposium on Advances in Automotive Control,  July 12-14, Munich, Germany / [ed] Ansgar Trächtler and Dirk Abel, 2010, p. 93-98Conference paper, Published paper (Refereed)
    Abstract [en]

    Designing diagnosis systems for hybrid vehicles include new features compared to conventional vehicles, e.g. mode switches in the system. The influence of this on the performance of the diagnosis system is investigated by design and implementation of diagnosis systems on vehicle level. The diagnosis systems are based on two sensor configurations, one consisting of many sensors and one of few sensors. The diagnosis systems detect specific faults, here specifically faults in the electrical components in a hybrid vehicle driveline, but the methodology is generic. There is a connection between the design of the energy management and the diagnosis system, and this interplay is of special relevance when models of components are valid only in some operating modes. In the systems implemented, the diagnosis system based on few sensors is more complex and includes a larger part of the vehicle model than the system based on more sensors.

    Series
    Advances in Automotive Control, ISSN 1474-6670
    Keywords
    sensor placement; sensor configuration; dynamic residual generator; parallel hybrid
    National Category
    Vehicle Engineering
    Identifiers
    urn:nbn:se:liu:diva-73890 (URN)10.3182/20100712-3-DE-2013.00128 (DOI)978-3-902661-72-2 (ISBN)
    Conference
    6th IFAC Symposium on Advances in Automotive Control, July 12-14, Munich, Germany
    Available from: 2012-01-16 Created: 2012-01-16 Last updated: 2014-03-25Bibliographically approved
    2. A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis
    Open this publication in new window or tab >>A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis
    2015 (English)In: International Journal of Modelling, Identification and Control, ISSN 1746-6172, Vol. 24, no 1, p. 1-9Article in journal (Refereed) Published
    Abstract [en]

    With the electrification of society, especially transportation, the control and supervision of electrical machines become more and more important due to its bearing on energy, environment, and safety. To optimise performance in control and supervision, appropriate modelling is crucial, and this regards both the ability to capture reality and the computational complexity to be useful in real-time. Here, a new low complexity model of the electric machine is proposed and developed. The new model treats the machine constants in a different way compared to a previous standard model, which results in a different expression for power losses. It is shown that this increases model expressiveness so when adapted to real data the result is significantly better. The significance of this modelling improvement is demonstrated using a task in vehicle diagnosis where it is shown that the separation between the non-faulty and faulty cases is better and the resulting performance is improved.

    Place, publisher, year, edition, pages
    InderScience Publishers, 2015
    Keywords
    electric machine models, permanent magnet synchronous machine, PMSM, power losses, hybrid electric vehicle, HEV, fault diagnosis, vehicle level diagnosis
    National Category
    Vehicle Engineering
    Identifiers
    urn:nbn:se:liu:diva-105485 (URN)10.1504/IJMIC.2015.071704 (DOI)
    Note

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

    Available from: 2014-03-25 Created: 2014-03-25 Last updated: 2018-11-27Bibliographically approved
    3. Selecting and Utilizing Sequential Residual Generators in FDI Applied to Hybrid Vehicles
    Open this publication in new window or tab >>Selecting and Utilizing Sequential Residual Generators in FDI Applied to Hybrid Vehicles
    2014 (English)In: IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, ISSN 2168-2216, Vol. 44, no 2, p. 172-185Article in journal (Refereed) Published
    Abstract [en]

    In order to obtain a realistic model of a complex system, thousands of possible residual generators need to be used for diagnosis. Based on engineering insights of the system to be monitored, certain algebraic and dynamic properties of the residual generators may be preferred, and therefore, a method for finding sequential residual generators is developed that accounts for these properties of the residual generator candidates. It is shown that only a small fraction of all residual generator candidates fulfill fundamental requirements, and thereby, proves the value of systematic methods. Furthermore, methods are devised for utilization of the residual generators, such as initialization of dynamic residual generators. A proposed method, considering the fault excitation in the residuals using the internal form of the residuals, significantly increases the diagnosis performance. A hybrid electric vehicle is used in a simulation study for demonstration, but the methods used are general in character and provides a basis when designing diagnosis systems for other complex systems.

    Place, publisher, year, edition, pages
    IEEE, 2014
    Keywords
    Fault diagnosis; hybrid electric vehicle; model based diagnosis; residual generation
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-104283 (URN)10.1109/TSMC.2013.2248147 (DOI)000330131800004 ()
    Available from: 2014-02-17 Created: 2014-02-14 Last updated: 2014-03-25
    4. Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle
    Open this publication in new window or tab >>Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle
    2014 (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    A common situation in the automotive industry is that map based models are available. In general these models accurately describe the fault free system, and are therefore suited for fault detectability in a diagnosis system. However, one drawback using such a model is that fault isolation then requires that measurements of the faulty system is done, which is costly. Another approach is to use a model of the system where the faults are explicitly included. To directly achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models are used in combination to achieve both good fault detectability and isolability in a diagnosis system; one is a map based model, and one is describing how the faults affect the system. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid electric vehicle. In an extensive simulation study it is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In the designed diagnosis system all faults are fully isolated, and the size of the faults are accurately estimated.

    National Category
    Vehicle Engineering
    Identifiers
    urn:nbn:se:liu:diva-105486 (URN)
    Available from: 2014-03-25 Created: 2014-03-25 Last updated: 2014-03-25Bibliographically approved
  • 7.
    Sundström, Christofer
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Vehicle Level Diagnosis for Hybrid Powertrains2011Licentiate thesis, monograph (Other academic)
    Abstract [en]

    There are possibilities to reduce the fuel consumption in trucks using hybrid technology. New components are added when hybridizing a vehicle, and these need to be monitored due to safety and legislative demands. Diagnosis aspects due to hybridization of the powertrain are investigated using a model of a long haulage truck. Such aspects are for example that there are more mode switches in the hybrid powertrain compared to a conventional vehicle, and there is a freedom in choosing operating points of the components in the powertrain via the energy management and still fulfill the torque request of the driver.

    To investigate the influence of energy management and sensor configuration on the performance of the diagnosis system, three diagnosis systems on vehicle level are designed and implemented. The systems are based on different sensor configurations; one with a fairly typical sensor configuration, one with the same number of sensors but in model sense placed more closely to the components to be monitored, and one with the minimal number of sensors to ideally achieve full fault isolability. It is found that there is a connection between the design of the energy management and the diagnosis systems, and that this connection is of special relevance when the model used in the diagnosis is valid only for some operating modes of the powertrain.

    In consistency based diagnosis it is investigated if there exists a solution to a set of equations with analytical redundancy, where the redundancy is obtained using measurements. The selection of sets of equations to be included in the diagnosis and how and in what order the unknown variables are to be computed affect the diagnosis performance. A simplified vehicle model is used to exemplify how an algebraic loop can be avoided for one computational sequence of the unknowns, but can not be avoided for a different computational sequence given the same overdetermined set of model equations. A vehicle level diagnosis system is designed using a systematic method to obtain unique residuals and that no signal is differentiated. The performance of the designed system is evaluated in a simulation study, and compared to a diagnosis system based on the same sets of equations, but where the residual generators are selected ad hoc. The results of the comparison are positive, which reinforces the idea of considering the properties of the residual generators in a systematic way.

    A diagnosis system using a map based model of the electric machine is designed. The benefits of using map based models are that it is easy to construct the models if measurements are available, and that such models in general are accurate. As a consequence of the structure of the model, full fault isolability is not possible to achieve using only the model for fault free behavior of the machine. To achieve full fault isolability, fault models are added to the diagnosis system using a model with a different model structure. The system isolates the faults, even though the induced faults are small in the simulation study, and the size of the faults are accurately estimated using observers.

  • 8.
    Sundström, Christofer
    et al.
    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.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis2015In: International Journal of Modelling, Identification and Control, ISSN 1746-6172, Vol. 24, no 1, p. 1-9Article in journal (Refereed)
    Abstract [en]

    With the electrification of society, especially transportation, the control and supervision of electrical machines become more and more important due to its bearing on energy, environment, and safety. To optimise performance in control and supervision, appropriate modelling is crucial, and this regards both the ability to capture reality and the computational complexity to be useful in real-time. Here, a new low complexity model of the electric machine is proposed and developed. The new model treats the machine constants in a different way compared to a previous standard model, which results in a different expression for power losses. It is shown that this increases model expressiveness so when adapted to real data the result is significantly better. The significance of this modelling improvement is demonstrated using a task in vehicle diagnosis where it is shown that the separation between the non-faulty and faulty cases is better and the resulting performance is improved.

  • 9.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    A Platform for Overall Monitoring and Diagnosis for Hybrid Vehicles2010Report (Other academic)
    Abstract [en]

    Compared with conventional vehicles, designing hybrid electric vehicles includes new features, such as energy management and monitoring of the electrical components. To be able to investigate such issues a simulation platform of a hybrid vehicle, driver, and diagnosis system is developed based on the CAPSim model library. The simulation platform is component based, and is able to handle different powertrain configurations. In this investigation a parallel hybrid is modeled and parameterized to represent a long haulage truck. To be able to easily change a model of a component in the vehicle model, every model of a specific component use the same sets of input and output signals. The vehicle model is based on dynamic equations and in general simple models of the components, since the interplay of the components is of major interest in this investigation. Three model based diagnosis systems are developed and implemented in the platform with a twofolded purpose. The first purpose is to demonstrate the feasibility of the platform. The second purpose is to investigate issues when designing diagnosis systems on vehicle level of a hybrid vehicle powertrain. New features, for example mode switches in the system and a freedom in choosing operating points of the components via the energy management, affect the diagnosis system. The influence of these issues on the performance of the diagnosis system is investigated by design and implementation of three diagnosis systems on a vehicle level. The diagnosis systems are based on three sensor configurations. Two of these consist of several sensors and one system uses few sensors. In one of the systems using information from several sensors, the sensors are placed close to the components that are to be monitored, while the sensors in the other system is based on a different sensor configuration. All three diagnosis systems detect specific faults, here specifically faults in the electrical components in a hybrid vehicle powertrain, but the methodology is generic. It is shown that there is a connection between the design of the energy management and the three diagnosis systems, and that this interplay is of special relevance when models of components are valid only in some operating modes. The diagnosis system based on few sensors is more complex and includes a larger part of the vehicle model than the system based on several sensors placed close to the components to be monitored.

  • 10.
    Sundström, Christofer
    et al.
    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.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle2014Manuscript (preprint) (Other academic)
    Abstract [en]

    A common situation in the automotive industry is that map based models are available. In general these models accurately describe the fault free system, and are therefore suited for fault detectability in a diagnosis system. However, one drawback using such a model is that fault isolation then requires that measurements of the faulty system is done, which is costly. Another approach is to use a model of the system where the faults are explicitly included. To directly achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models are used in combination to achieve both good fault detectability and isolability in a diagnosis system; one is a map based model, and one is describing how the faults affect the system. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid electric vehicle. In an extensive simulation study it is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In the designed diagnosis system all faults are fully isolated, and the size of the faults are accurately estimated.

  • 11.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Diagnostic Method Combining the Lookup Tables and Fault Models Applied on a Hybrid Electric Vehicle2016In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 24, no 3, p. 1109-1117Article in journal (Refereed)
    Abstract [en]

    A common situation in industry is to store measurements for different operating points in the lookup tables, often called maps. They are used in many tasks, e.g., in control and estimation, and therefore considerable investments in engineering time are spent in measuring them which usually make them accurate descriptions of the fault-free system. They are thus well suited for fault detection, but, however, such a model cannot give fault isolation since only the fault free behavior is modeled. One way to handle this situation would be also to map all fault cases but that would require measurements for all faulty cases, which would be costly if at all possible. Instead, the main contribution here is a method to combine the lookup model with analytical fault models. This makes good use of all modeling efforts of the lookup model for the fault-free case, and combines it with fault models with reasonable modeling and calibration efforts, thus decreasing the engineering effort in the diagnosis design. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid electric vehicle. An extensive simulation study clearly shows that the approach achieves both good fault detectability and isolability performance. A main point is that this is achieved without the need for neither measurements of a faulty system nor detailed physical modeling, thus saving considerable amounts of development time.

  • 12.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Fault Monitoring of the Electric Machine in a Hybrid Vehicle2013In: Proceedings of the 7th IFAC Symposium on Advances in Automotive Control, The International Federation of Automatic Control, Elsevier, 2013, Vol. 46, no 21, p. 548-553Conference paper (Refereed)
    Abstract [en]

    A diagnosis system for the electric machine and the power electronics in a hybrid electric vehicle is designed, where the diagnosis system uses a map based model of the system to be monitored. Such a model gives an accurate description of the fault free system, and is therefore suited for fault detectability. However, one drawback using such a model for diagnosis is that fault isolation often requires that the model, in addition to the fault free case, also describes the faulty system, and thereby measurements of the faulty system are needed, which is costly. Another approach is to use a model including physical parameters of interest in the system to be monitored, to also describe the faults’ impact on the system. To achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models for the system are used in combination to achieve good fault detectability and isolability; one is a map based model, and one is describing the faults of the system. It is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In a simulation study evaluating the designed diagnosis system all faults are isolated and also accurately estimated.

  • 13.
    Sundström, Christofer
    et al.
    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.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Overall Monitoring and Diagnosis for Hybrid Vehicle Powertrains2010In: Proceedings of the 6th IFAC Symposium on Advances in Automotive Control,  July 12-14, Munich, Germany / [ed] Ansgar Trächtler and Dirk Abel, 2010, p. 93-98Conference paper (Refereed)
    Abstract [en]

    Designing diagnosis systems for hybrid vehicles include new features compared to conventional vehicles, e.g. mode switches in the system. The influence of this on the performance of the diagnosis system is investigated by design and implementation of diagnosis systems on vehicle level. The diagnosis systems are based on two sensor configurations, one consisting of many sensors and one of few sensors. The diagnosis systems detect specific faults, here specifically faults in the electrical components in a hybrid vehicle driveline, but the methodology is generic. There is a connection between the design of the energy management and the diagnosis system, and this interplay is of special relevance when models of components are valid only in some operating modes. In the systems implemented, the diagnosis system based on few sensors is more complex and includes a larger part of the vehicle model than the system based on more sensors.

  • 14.
    Sundström, Christofer
    et al.
    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.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Residual Generator Selection for Fault Diagnosis of Hybrid Vehicle Powertrains2011Conference paper (Refereed)
    Abstract [en]

    The performance of a model based diagnosis system is affected by the selection of consistency relation in a set of equations with analytical redundancy in a non-linear system. To investigate aspects due to this, two diagnosis systems of a parallel hybrid truck are designed, and both static and dynamic issues are considered. A simplified vehicle model is used to exemplify how a unique expression for the residual generator can be found for one selection of consistency relation, but not for others, using the same set of equations. A simulation study using the entire vehicle model is made to investigate how the performance in the diagnosis system is affected when dynamic equations are either differentiated or integrated. The diagnosis systems are designed using structural analysis in combination with the algebraic expressions. One key result is that it is not trivial to find a computational order by hand that fulfills the predefined conditions on the computational sequence, and therefore systematic methods are valuable.

  • 15.
    Sundström, Christofer
    et al.
    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.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Selecting and Utilizing Sequential Residual Generators in FDI Applied to Hybrid Vehicles2014In: IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, ISSN 2168-2216, Vol. 44, no 2, p. 172-185Article in journal (Refereed)
    Abstract [en]

    In order to obtain a realistic model of a complex system, thousands of possible residual generators need to be used for diagnosis. Based on engineering insights of the system to be monitored, certain algebraic and dynamic properties of the residual generators may be preferred, and therefore, a method for finding sequential residual generators is developed that accounts for these properties of the residual generator candidates. It is shown that only a small fraction of all residual generator candidates fulfill fundamental requirements, and thereby, proves the value of systematic methods. Furthermore, methods are devised for utilization of the residual generators, such as initialization of dynamic residual generators. A proposed method, considering the fault excitation in the residuals using the internal form of the residuals, significantly increases the diagnosis performance. A hybrid electric vehicle is used in a simulation study for demonstration, but the methods used are general in character and provides a basis when designing diagnosis systems for other complex systems.

  • 16.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Blom, Anders
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Analysis of optimal energy management in smart homes using MPC2016In: 2016 EUROPEAN CONTROL CONFERENCE (ECC) , Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 2066-2071Conference paper (Refereed)
    Abstract [en]

    Advanced building management systems utilize future information, such as electricity spot prices, weather forecasts, and predicted electric loads and hot water consumption, to reduce the maximum electric power consumption and energy cost. A model predictive controller (MPC) is implemented for a household with one hour sample intervals, including hot water usage, charging of an electric vehicle, and domestic heating, but also an accumulator water tank to be used as an additional thermal energy storage. Both the maximum total power used in the house and the energy cost are included in the cost function to evaluate how these properties are affected by different system designs. The MPC solution is compared to the global optimal solution using dynamic programming indicating comparable performance. The robustness of the MPC is evaluated using a prediction of the future household electric consumption in the controller. Results also show that a significant part of the cost reduction is achieved for as small prediction horizons as five hours. Analysis shows that including an accumulator tank is useful for reducing the total energy cost, while reducing the peak power is mainly achieved by increasing the prediction horizon of the MPC.

  • 17.
    Sundström, Christofer
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Smart Energy Usage for Vehicle Charging and House Heating2015Conference paper (Refereed)
    Abstract [en]

    In northern Europe the electricity price is set by hourly rates one day in advance. The price fluctuates due to supply and demand, and these fluctuations are expected to increase when solar and wind power are increased in the energy system. The potential in cost reduction for heating a house and charging of an electrified vehicle by using a smart energy management system in a household is investigated. Dynamic programming is used and a simulation study of a household in Sweden comparing this optimal control scheme with a heuristic controller is carried out. The time frame in the study is one year and a novel way of handling the fact that the vehicle is disconnected from the grid at some times is developed. A plug-in hybrid electric vehicle is considered, but the methodology is the same also for pure electric vehicles. It is found that the potential in energy cost reduction for house heating and vehicle charging is significant and that using a smart energy management system is a promising path of cost reduction, especially with the introduction of electrified vehicles. 

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