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  • 251.
    Jia Wei Tang, Samuel
    et al.
    Monash University, Australia.
    Ng, Kok Yew
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering. Monash University, Malaysia.
    Khoo, BH
    Monash University, Malaysia.
    Parkkinen, Jussi
    University of Eastern Finland, Finland.
    Real-Time Lane Detection and Rear-End Collision Warning System On A Mobile Computing Platform2015In: 39TH ANNUAL IEEE COMPUTERS, SOFTWARE AND APPLICATIONS CONFERENCE (COMPSAC 2015), VOL 2, IEEE , 2015, p. 563-568Conference paper (Refereed)
    Abstract [en]

    Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rear-end collision warning system for drivers on the road. The Android-based application uses image-processing algorithms coupled with the monoscopic camera on the smartphone as the main sensor to perform lane and vehicle detections. The novelty of this work lies in the use of the monocular vision of the camera to estimate the distance with the vehicle up ahead. The system is able to distinguish unintentional lane departure and if the driver is traveling too close to the vehicle ahead. An acoustic warning will notify the driver of a potential accident.

  • 252.
    Johansson, Andreas
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Kvaldén, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Prestandaförbättring på en semiaktiv dämpare genom förbättrad reglering2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [sv]

    Hydrauliska stötdämpare har länge varit en central komponent på både bilar och motorcyklar. Stötdämpare påverkar fordonets komfort, väghållning och köregenskaper. Dessa olika egenskaper kräver ofta helt olika typer av dämpning och med vanliga passiva dämpare blir resultatet ofta en kompromiss av samtliga dessa. Kompromisserna har lett till utvecklingen av en stötdämpare med ställbar dämparkarakteristik som är tänkt att ersätta passiva dämpare. Öhlins Racing säljer idag ett semiaktivt stötdämparsystem som kallas CES, Continously controlled Electronic Suspension, där dämparkarakteristiken styrs av en tryck- och flödeskompenserad CES-ventil. CES-ventilen är strömstyrd via en ECU, Electronic Control Unit, som monteras på fordonet. Möjligheterna att förbättra fordonens egenskaper är stora men regleringen av dämparen är kritisk för prestandan.

    Examesarbetet syftar till att via experimentella laborationstester förbättra dämparens prestanda genom att förbättra styrningen av systemet. Det visar sig att den nuvarande reglersystemet lider av en tidsfördröjning, varför en stor del av examensarbetet fokuserar på att minimera detta.

    Resultaten visar att då hastigheten skattas med ett Kalmanfilter, som tar hänsyn till både dämparens position och acceleration, kan tidsfördröjningar nästan helt elimineras. Elimineringen av tidsfördröjning visar sig förbättra prestandan avsevärt. För att ytterligare öka prestandan hos systemet introduceras även en accelerationsframkoppling.

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  • 253.
    Johansson, Anton
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Drangel, Martin
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Measurements and Modelling for Heat Transfer Corrected Exhaust Gas Temperatures in a Gasoline Engine2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis is treating the modelling of a thermocouple (tc) to compensate forheat transfers due to convection, radiation and conduction when performingtemperature measurements in an SI-engine. An experiment plan was developedwhich covered experiments in an stc-rig and on a 4-cylinder SI-engine. The measurementsin the stc-rig was mainly to develop the model, while the measurementsin the engine lab was mainly to examine the characteristics of the engineand evaluate the modelled tc.Measurements with an exposed thin tip tc in the stc-rig showed a symmetricaltemperature profile in the pipe. By examining how the 1.5 mm tc behaved inthis environment with known gas temperature profile, the obtained knowledgecould be applied to cross-sectional measurements in the SI-engine. It was foundthat the temperature profile in the engine deviated from the temperature profilemeasured in the stc-rig. The temperature was higher near the top of the pipethan in the center and lower part. In the horizontal direction, the temperaturewas found to be constant.Conclusions drawn from measurements in the engine lab points to that the crosssectionaltemperature and mass flow profiles have a strong connection with theengine’s operation point. The cross-sectional profiles, along with respective profileover time, is crucial when estimating the energy content of an exhaust gaspulse.The inverted sensor model with optimized parameters could estimate the meanvalue of the measured gas temperature during stationary runs within 6 degC.

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  • 254.
    Johansson, Henrik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Evaluation of Communication Interfaces for ElectronicControl Units in Heavy-duty Vehicles2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The number of electronic control units in heavy-duty vehicles has grown dramatically overthe last few decades. This has led to the use of communication buses to reduce the complexityand weight of the networks. There are reasons to believe that the de facto standardcommunication interface in the automotive industry, the Controller Area Network, is obsoletein some areas. Hence an evaluation of available communication interfaces is needed.This study focuses on lower levels of the Open Systems Interconnect (osi) model. Initially atheoretical study is presented in order to give an overview of automotive embedded systemsin general and different communication interfaces in particular. Ethernet and FlexRay areidentified as two interfaces of interest for future use in Scanias vehicles. The former is new inautomotive applications but is believed to become popular over the years to come. A possibleuse of this interface could be as a backbone to take the load off other interfaces. The use ofFlexRay in Scanias vehicles is limited because of the modular system used and the staticscheduling needed. It could however be used between mandatory ecus where the nodes andthe messages are all known beforehand.The report also contains the result from emission measurements on a number of interfacesperformed using a stripline antenna in a shielded enclosure. Strong conclusions can not bedrawn since it’s hard to tell what the transceivers, circuit boards and interfaces contributedto in the spectra with the method used. The FlexRay hardware is worse than for the otherinterfaces. Similarities can be seen between low-speed and high-speed can but it could becharacteristics of the transceivers used rather than the interface itself.

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  • 255.
    Johansson, Linus
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Full Cycle Cylinder State Estimation in DI Engines with VVA2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Tougher legal demands on pollutions require a better developed understanding of the processes that take place in the cylinder. The thesis contributes with a cylinder model that uses the same set of equations for intake, compression,expansion/combustion and exhaust. The cylinder model describes the states temperature, pressure and the mass fraction of air.The model is able to simulate the gas exchange with compressible flows over the valves, it handles VVT, CRB and blowby. The combustion is modeled with asingle Vibe function that describes the heat release and the consumption of air.The model is general enough to be able to simulate both SI and CI engines. The calibrations that are needed are the discharge coefficient CD values for intake and exhaust valves, blowby, and heat release/transfer parameters. Furthermore, the engine geometry parameters have to be provided to be able to calculate the instanteneous cylinder volume. The model has shown good agreement for cylinder pressure curves with and without combustion and can handle phasingof the valve lifts. That shows that the model can handle the important casesin combustion engines. It is easy to replace sub models in the cylinder model e.g. single Vibe with double Vibe. In the model, in the cylinder is calculated and the average instantenous torque for the entire engine is calculated from thestates in one cylinder. These two calculations have shown good agreement withthe stationary measurments done in an engine test cell. The model is able to use fixed step lengths for even processor loads, the size of the step lengths are resonable for real time implementation on an ECU.

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  • 256.
    Johansson, Max
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Optimal Control of Heat Transfer Rates in Turbochargers2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The turbocharger is an important component of competitive environmentally friendly vehicles. Mathematical models are needed for controlling turbochargers in modern vehicles. The models are parameterized using data, gathered from turbocharger testing ingas stands (a flow bench for turbocharger, where the engine is replaced with a combustion chamber, so that the exhaust gases going to the turbocharger can be controlled with high accuracy). Collecting the necessary time averaged data is a time-consuming process. It can take more than 24 hours per turbocharger. To achieve a sufficient level of accuracy in the measurements, it is required to let the turbocharger system reach steady state after a change of operating point. The turbocharger material temperatures are especially slow to reach steady state.

    A hypothesis is that modern methods in control theory, such as numeric optimal control, can drastically reduce the wait time when changing operating point. The purpose of this thesis is to provide a method of time optimal testing of turbo chargers.

     Models for the turbine, bearing house and compressor are parameterized. Well known models for heat transfer is used to describe the heat flows to and from exhaust gas and charge air, and turbocharger material, as well as internal energy flows between the turbocharger components. The models, mechanical and thermodynamic, are joined to form a complete turbocharger model, which is validated against measured step responses.

    Numeric optimal control is used to calculate optimal trajectories for the turbo charger input signals, so that steady state is reached as quickly as possible, fora given operating point. Direct collocation is a method where the optimal control problem is discretized, and a non-linear program solver is used. The results show that the wait time between operating points can be reduced by a factor of 23.

    When optimal trajectories between operating points can be found, the possibility of further gains, if finding an optimal sequence of trajectories, are investigated. The problem is equivalent to the open traveling salesman, a well studied problem, where no optimal solution can be guaranteed. A near optimal solution is found using a genetic algorithm.

    The developed method requires a turbocharger model to calculate input trajectories. The testing is done to acquire data, so that a model can be created, which is a catch-22 situation. It can be avoided by using system identification techniques. When the gas stand is warming up, the necessary model parameters are estimated, using no prior knowledge of the turbocharger.

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  • 257.
    Johansson, Max
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Ekberg, Kristoffer
    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.
    Time Optimal Turbocharger Testing in Gas Stands with a Known Map2018In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2018, Vol. 51, no 31, p. 868-875Conference paper (Refereed)
    Abstract [en]

    Turbocharger maps are used in design, evaluation and optimization of engine system operation to represent the turbo operation in different scenarios. To construct such a map, the turbo is tested in a gas flow test bench, called gas stand. Turbo testing is a time and resource consuming experimental process. The turbo is tested in a selected number of test points for different turbo rotational speeds, where the temperatures in the turbo have to be stationary when the measurements that constitute the map are acquired. In this paper, optimal control is used to find the most time efficient pattern of test conditions, and the optimal control strategy to traverse between them. A heat transfer model, describing the heat transfer between the compressor, bearing house, and turbine, is presented and validated against measured data. A direct collocation method is used to find time optimal control trajectories between the specified test points in the map. The method objective is to find the least time consuming control strategy which brings the turbo from one test point to the next, while ensuring thermal equilibrium at the final time. The results suggest that this method reduces turbocharger testing time with a factor higher than 60. The improvements can be further increased, with over 70 times, if a traveling salesman problem is solved to find the optimal route through the turbo map. The described method would be able to map a 43 points turbo map in 22 minutes, including a 5 minute warm-up phase. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 258.
    Johansson, Tobias
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Virtual Sensors for Combustion Parameters Based on In-Cylinder Pressure2015Independent thesis Advanced level (degree of Master (Two Years)), 300 HE creditsStudent thesis
    Abstract [en]

    Typically the combustion in engines are open-loop controlled. By using an in-cylinder pressure sensor it is possible to create virtual sensors for closed-loop combustion control (CLCC). With CLCC it is possible to counteract dynamic effects as component ageing, fuel type and cylinder variance.

    A virtual sensor system was implemented based on a one-zone heat-release analysis, including signal processing of the pressure sensor input. A parametrisation of the heat-release based on several Vibe functions was implemented with good results.

    The major focus of the virtual sensor system was to perform a tolerance analysis on experimental data, where typical error sources in a production heavy-duty vehicle were identified and their effect on the estimates quantified. It could be concluded that estimates are very much dependent on the choice of heat-release and specific heat ratio models. Especially crank angle phasing has a large impact on estimation performance, stressing the importance of accounting for crankshaft torsion in production vehicles. Biodiesel advances the combustion angle and give a lower IMEP and total heat amount compared to standard diesel. However, error sensitivity is not affected.

    Further investigations must be made on improving the signal processing in terms of gain error compensation and filtering. Also a better understanding of how errors propagate between subsystems in a CLCC system is required for successful implementation.

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  • 259.
    Jonsson Holm, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Vehicle Mass and Road Grade Estimation Using Kalman Filter2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This Master's thesis presents a method for on-line estimation of vehicle mass and road grade using Kalman filter. Many control strategies aiming for better fuel economy, drivability and safety in today's vehicles rely on precise vehicle operating information. In this context, vehicle mass and road grade are crucial parameters. The method is based on an extended Kalman filter (EKF) and a longitudinal vehicle model. The main advantage of this method is its applicability on drivelines with continuous power output during gear shifts and cost effectiveness compared to hardware solutions. The performance has been tested on both simulated data and on real measurement data, collected with a truck on road. Two estimators were developed; one estimates both vehicle mass and road grade and the other estimates only vehicle mass using an inclination sensor as an additional measurement. Tests of the former estimator demonstrate that a reliable mass estimate with less than 5 % error is often achievable within 5 minutes of driving. Furthermore, the root mean square error of the grade estimate is often within 0.5°. Tests of the latter estimator show that this is more accurate and robust than the former estimator with a mass error often within 2 %. A sensitivity analysis shows that the former estimator is fairly robust towards minor modelling errors. Also, an observability analysis shows under which circumstances simultaneous vehicle mass and road grade is possible.

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    Vehicle Mass and Road Grade Estimation Using Kalman Filter
  • 260.
    Juhlin, Olof
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Modeling of Battery Degradation in Electrified Vehicles2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis provides an insight into battery modeling in electric vehicles which includes degradation mechanisms as in automotive operation in electric vehicles. As electric vehicles with lithium ion batteries increase in popularity there is an increased need to study and model the capacity losses in such batteries. If there is a good understanding of the phenomena involved and an ability to predict these losses there is also a foundation to take measures to minimize these losses.

    In this thesis a battery model for lithium ion batteries which includes heat dissipation is used as groundwork. This model is expanded with the addition of capacity losses due to usage as well as storage. By combining this with a simple vehicle model one can use these models to achieve an understanding as to how a battery or pack of several batteries would behave in a specific driving scenario. Much of the focus in the thesis is put into comparing the different factors of degradation to highlight what the major contributors are.

    The conclusion is drawn that heat is the main cause for degradation for batteries in electric vehicles. This applies for driving usage as well as during storage. As heat is generated when a battery is used, the level of current is also a factor, as well as in which state of charge region the battery is used.

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  • 261.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    A generalized fault isolability matrix for improved fault diagnosability analysis2016In: 2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), IEEE , 2016, p. 519-524Conference paper (Refereed)
    Abstract [en]

    A generalized fault isolability matrix is proposed for quantitative analysis of fault isolability properties. The original fault isolability matrix gives information about which faults that are isolable from each other. However, other relavant isolability properties are not visible which can be important, for example, information regarding alternative fault hypotheses and multiple-fault isolability. The result of the analysis can be presented in the same compact form as the existing fault isolability matrix which makes it simple to visualize. As a case study, a model of an internal combustion engine is analyzed and two different solutions to the test selection problem are compared.

  • 262. Order onlineBuy this publication >>
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Diagnosability performance analysis of models and fault detectors2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Model-based diagnosis compares observations from a system with predictions using a mathematical model to detect and isolate faulty components. Analyzing which faults that can be detected and isolated given the model gives useful information when designing a diagnosis system. This information can be used, for example, to determine which residual generators can be generated or to select a sufficient set of sensors that can be used to detect and isolate the faults. With more information about the system taken into consideration during such an analysis, more accurate estimations can be computed of how good fault detectability and isolability that can be achieved.

    Model uncertainties and measurement noise are the main reasons for reduced fault detection and isolation performance and can make it difficult to design a diagnosis system that fulfills given performance requirements. By taking information about different uncertainties into consideration early in the development process of a diagnosis system, it is possible to predict how good performance can be achieved by a diagnosis system and avoid bad design choices. This thesis deals with quantitative analysis of fault detectability and isolability performance when taking model uncertainties and measurement noise into consideration. The goal is to analyze fault detectability and isolability performance given a mathematical model of the monitored system before a diagnosis system is developed.

    A quantitative measure of fault detectability and isolability performance for a given model, called distinguishability, is proposed based on the Kullback-Leibler divergence. The distinguishability measure answers questions like "How difficult is it to isolate a fault fi from another fault fj?. Different properties of the distinguishability measure are analyzed. It is shown for example, that for linear descriptor models with Gaussian noise, distinguishability gives an upper limit for the fault to noise ratio of any linear residual generator. The proposed measure is used for quantitative analysis of a nonlinear mean value model of gas flows in a heavy-duty diesel engine to analyze how fault diagnosability performance varies for different operating points. It is also used to formulate the sensor selection problem, i.e., to find a cheapest set of available sensors that should be used in a system to achieve required fault diagnosability performance.

    As a case study, quantitative fault diagnosability analysis is used during the design of an engine misfire detection algorithm based on the crankshaft angular velocity measured at the flywheel. Decisions during the development of the misfire detection algorithm are motivated using quantitative analysis of the misfire detectability performance showing, for example, varying detection performance at different operating points and for different cylinders to identify when it is more difficult to detect misfires.

    This thesis presents a framework for quantitative fault detectability and isolability analysis that is a useful tool during the design of a diagnosis system. The different applications show examples of how quantitate analysis can be applied during a design process either as feedback to an engineer or when formulating different design steps as optimization problems to assure that required performance can be achieved.

    List of papers
    1. A method for quantitative fault diagnosability analysis of stochastic linear descriptor models
    Open this publication in new window or tab >>A method for quantitative fault diagnosability analysis of stochastic linear descriptor models
    2013 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 49, no 6, p. 1591-1600Article in journal (Refereed) Published
    Abstract [en]

    Analyzing fault diagnosability performance for a given model, before developing a diagnosis algorithm, can be used to answer questions like “How difficult is it to detect a fault fi?” or “How difficult is it to isolate a fault fi from a fault fj?”. The main contributions are the derivation of a measure, distinguishability, and a method for analyzing fault diagnosability performance of discrete-time descriptor models. The method, based on the Kullback–Leibler divergence, utilizes a stochastic characterization of the different fault modes to quantify diagnosability performance. Another contribution is the relation between distinguishability and the fault to noise ratio of residual generators. It is also shown how to design residual generators with maximum fault to noise ratio if the noise is assumed to be i.i.d. Gaussian signals. Finally, the method is applied to a heavy duty diesel engine model to exemplify how to analyze diagnosability performance of non-linear dynamic models.

    Place, publisher, year, edition, pages
    Elsevier, 2013
    Keywords
    Fault diagnosability analysis; Fault detection and isolation; Model-based diagnosis
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-89941 (URN)10.1016/j.automatica.2013.02.045 (DOI)000319540500007 ()
    Available from: 2013-03-11 Created: 2013-03-11 Last updated: 2019-09-23Bibliographically approved
    2. Asymptotic behavior of fault diagnosis performance
    Open this publication in new window or tab >>Asymptotic behavior of fault diagnosis performance
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Fault detection and fault isolation performance of a model based diagnosis system mainly depends on the level of model uncertainty and the time allowed for detection. The longer time for detection that can be accepted, the more certain detection can be achieved and the main objective of this paper is to show how the window length relates to diagnosis performance. A key result is an explicit expression for asymptotic performance with respect to window length. A key property of the approach is that the model is analyzed directly, which makes the approach independent of detection filter design. It is shown that there exists a linear asymptote as the window length tends to infinity and it is also shown how this linear asymptote can be computed as well as higher order approximations.

    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-117174 (URN)
    Available from: 2015-04-21 Created: 2015-04-21 Last updated: 2015-04-21Bibliographically approved
    3. Quantitative isolability analysis of different fault modes
    Open this publication in new window or tab >>Quantitative isolability analysis of different fault modes
    2015 (English)In: 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 – Paris, 2–4 September 2015: Proceedings / [ed] Didier Maquin, Elsevier, 2015, Vol. 48(21), p. 1275-1282Conference paper, Published paper (Refereed)
    Abstract [en]

    To be able to evaluate quantitative fault diagnosability performance in model-based diagnosis is useful during the design of a diagnosis system. Different fault realizations are more or less likely to occur and the fault diagnosis problem is complicated by model uncertainties and noise. Thus, it is not obvious how to evaluate performance when all of this information is taken into consideration. Four candidates for quantifying fault diagnosability performance between fault modes are discussed. The proposed measure is called expected distinguishability and is based of the previous distinguishability measure and two methods to compute expected distinguishability are presented.

    Place, publisher, year, edition, pages
    Elsevier, 2015
    Series
    IFAC-PapersOnLine, ISSN 2405-8963
    Keywords
    Fault detection and isolation, quantitative diagnosability analysis, Kullback-Leibler divergence
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Computer Engineering
    Identifiers
    urn:nbn:se:liu:diva-117175 (URN)10.1016/j.ifacol.2015.09.701 (DOI)
    Conference
    9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 – Paris, France, 2–4 September 2015
    Note

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

    Available from: 2015-04-21 Created: 2015-04-21 Last updated: 2019-09-23Bibliographically approved
    4. Sensor selection for fault diagnosis in uncertain systems
    Open this publication in new window or tab >>Sensor selection for fault diagnosis in uncertain systems
    Show others...
    2020 (English)In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 93, no 3, p. 629-639Article in journal (Refereed) Published
    Abstract [en]

    Finding the cheapest, or smallest, set of sensors such that a specified level of diagnosis performance is maintained is important to decrease cost while controlling performance. Algorithms have been developed to find sets of sensors that make faults detectable and isolable under ideal circumstances. However, due to model uncertainties and measurement noise, different sets of sensors result in different achievable diagnosability performance in practice. In this paper, the sensor selection problem is formulated to ensure that the set of sensors fulfils required performance specifications when model uncertainties and measurement noise are taken into consideration. However, the algorithms for finding the guaranteed global optimal solution are intractable without exhaustive search. To overcome this problem, a greedy stochastic search algorithm is proposed to solve the sensor selection problem. A case study demonstrates the effectiveness of the greedy stochastic search in finding sets close to the global optimum in short computational time.

    Place, publisher, year, edition, pages
    Taylor & Francis, 2020
    Keywords
    Fault diagnosis, fault detection and isolation, sensor selection
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Computer Engineering
    Identifiers
    urn:nbn:se:liu:diva-117176 (URN)10.1080/00207179.2018.1484171 (DOI)000525971000025 ()
    Note

    The previous status of this article was Manuscript.

    Available from: 2015-04-21 Created: 2015-04-21 Last updated: 2020-05-05Bibliographically approved
    5. Development of misfire detection algorithm using quantitative FDI performance analysis
    Open this publication in new window or tab >>Development of misfire detection algorithm using quantitative FDI performance analysis
    2015 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 34, p. 49-60Article in journal (Refereed) Published
    Abstract [en]

    A model-based misfire detection algorithm is proposed. The algorithm is able to detect misfires and identify the failing cylinder during different conditions, such as cylinder-to-cylinder variations, cold starts, and different engine behavior in different operating points. Also, a method is proposed for automatic tuning of the algorithm based on training data. The misfire detection algorithm is evaluated using data from several vehicles on the road and the results show that a low misclassification rate is achieved even during difficult conditions. (C) 2014 Elsevier Ltd. All rights reserved.

    Place, publisher, year, edition, pages
    Elsevier, 2015
    Keywords
    Misfire detection; Fault diagnosis; Fault detection and isolation; Kullback-Leibler divergence; Pattern recognition
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-114011 (URN)10.1016/j.conengprac.2014.10.001 (DOI)000347599500005 ()
    Note

    Funding Agencies|Volvo Car Corporation; Swedish Research Council within the Linnaeus Center CADICS

    Available from: 2015-02-06 Created: 2015-02-05 Last updated: 2019-09-23
    6. A flywheel error compensation algorithm for engine misfire detection
    Open this publication in new window or tab >>A flywheel error compensation algorithm for engine misfire detection
    2016 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 47, p. 37-47Article in journal (Refereed) Published
    Abstract [en]

    A commonly used signal for engine misfire detection is the crankshaft angular velocity measured at the flywheel. However, flywheel manufacturing errors result in vehicle-to-vehicle variations in the measurements and have a negative impact on the misfire detection performance, where the negative impact is quantified for a number of vehicles. A misfire detection algorithm is proposed with flywheel error adaptation in order to increase robustness and reduce the number of mis-classifications. Since the available computational power is limited in a vehicle, a filter with low computational load, a Constant Gain Extended Kalman Filter, is proposed to estimate the flywheel errors. Evaluations using measurements from vehicles on the road show that the number of mis-classifications is significantly reduced when taking the estimated flywheel errors into consideration.

    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Computer Engineering
    Identifiers
    urn:nbn:se:liu:diva-117177 (URN)10.1016/j.conengprac.2015.12.009 (DOI)000370091900004 ()
    Note

    Funding agencies:The work is partially supported by the Swedish Research Council within the Linnaeus Center CADICS.

    Vid tiden för disputation förelåg publikationen endast som manuskript

    Available from: 2015-04-21 Created: 2015-04-21 Last updated: 2019-09-23Bibliographically approved
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  • 263.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Engine Fault Diagnosis Combining Model-based Residuals and Data-Driven Classifiers2019In: IFAC PAPERSONLINE, ELSEVIER , 2019, Vol. 52, no 5, p. 285-290Conference paper (Refereed)
    Abstract [en]

    Design of fault diagnosis systems is complicated by limited training data and inaccuracies in physical-based models when designing fault classifiers. A hybrid fault diagnosis approach is proposed using model-based residuals as input to a set of data-driven fault classifiers. As a case study, sensor data from an internal combustion engine test bed is used where faults have been injected into the system and a physical-based mathematical model of the air flow through the engine is available. First, a feature selection algorithm is applied to find a minimal set of residuals that is able to separate the different fault modes. Then, two different fault classification approaches are discussed, Random Forests and one-class Support Vector Machines. A set of one-class Support Vector Machines is used to model data from each fault mode separately. The case study illustrates an advantage of using one-class classifiers, which makes it possible to detect unknown faults by identifying samples not belonging to any known fault mode. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 264.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Dong, Yi
    Institute for Software Integrated Systems, Vanderbilt University, Nashville, USA.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Institute for Software Integrated Systems, Vanderbilt University, Nashville, USA.
    Sensor selection for fault diagnosis in uncertain systems2020In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 93, no 3, p. 629-639Article in journal (Refereed)
    Abstract [en]

    Finding the cheapest, or smallest, set of sensors such that a specified level of diagnosis performance is maintained is important to decrease cost while controlling performance. Algorithms have been developed to find sets of sensors that make faults detectable and isolable under ideal circumstances. However, due to model uncertainties and measurement noise, different sets of sensors result in different achievable diagnosability performance in practice. In this paper, the sensor selection problem is formulated to ensure that the set of sensors fulfils required performance specifications when model uncertainties and measurement noise are taken into consideration. However, the algorithms for finding the guaranteed global optimal solution are intractable without exhaustive search. To overcome this problem, a greedy stochastic search algorithm is proposed to solve the sensor selection problem. A case study demonstrates the effectiveness of the greedy stochastic search in finding sets close to the global optimum in short computational time.

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    Sensor selection for fault diagnosis in uncertain systems
  • 265.
    Jung, Daniel
    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.
    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.
    Development of misfire detection algorithm using quantitative FDI performance analysis2015In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 34, p. 49-60Article in journal (Refereed)
    Abstract [en]

    A model-based misfire detection algorithm is proposed. The algorithm is able to detect misfires and identify the failing cylinder during different conditions, such as cylinder-to-cylinder variations, cold starts, and different engine behavior in different operating points. Also, a method is proposed for automatic tuning of the algorithm based on training data. The misfire detection algorithm is evaluated using data from several vehicles on the road and the results show that a low misclassification rate is achieved even during difficult conditions. (C) 2014 Elsevier Ltd. All rights reserved.

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  • 266.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering. The Ohio State University, Columbus, OH, USA.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Residual selection for fault detection and isolation using convex optimization2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 97, p. 143-149Article in journal (Refereed)
    Abstract [en]

    In model-based diagnosis there are often more candidate residual generators than what is needed and residual selection is therefore an important step in the design of model-based diagnosis systems. The availability of computer-aided tools for automatic generation of residual generators have made it easier to generate a large set of candidate residual generators for fault detection and isolation. Fault detection performance varies significantly between different candidates due to the impact of model uncertainties and measurement noise. Thus, to achieve satisfactory fault detection and isolation performance, these factors must be taken into consideration when formulating the residual selection problem. Here, a convex optimization problem is formulated as a residual selection approach, utilizing both structural information about the different residuals and training data from different fault scenarios. The optimal solution corresponds to a minimal set of residual generators with guaranteed performance. Measurement data and residual generators from an internal combustion engine test-bed is used as a case study to illustrate the usefulness of the proposed method.

    The full text will be freely available from 2020-08-18 11:24
  • 267.
    Jung, Daniel
    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.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    A flywheel error compensation algorithm for engine misfire detection2016In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 47, p. 37-47Article in journal (Refereed)
    Abstract [en]

    A commonly used signal for engine misfire detection is the crankshaft angular velocity measured at the flywheel. However, flywheel manufacturing errors result in vehicle-to-vehicle variations in the measurements and have a negative impact on the misfire detection performance, where the negative impact is quantified for a number of vehicles. A misfire detection algorithm is proposed with flywheel error adaptation in order to increase robustness and reduce the number of mis-classifications. Since the available computational power is limited in a vehicle, a filter with low computational load, a Constant Gain Extended Kalman Filter, is proposed to estimate the flywheel errors. Evaluations using measurements from vehicles on the road show that the number of mis-classifications is significantly reduced when taking the estimated flywheel errors into consideration.

  • 268.
    Jung, Daniel
    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.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, The Institute of Technology.
    Quantitative isolability analysis of different fault modes2015In: 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 – Paris, 2–4 September 2015: Proceedings / [ed] Didier Maquin, Elsevier, 2015, Vol. 48(21), p. 1275-1282Conference paper (Refereed)
    Abstract [en]

    To be able to evaluate quantitative fault diagnosability performance in model-based diagnosis is useful during the design of a diagnosis system. Different fault realizations are more or less likely to occur and the fault diagnosis problem is complicated by model uncertainties and noise. Thus, it is not obvious how to evaluate performance when all of this information is taken into consideration. Four candidates for quantifying fault diagnosability performance between fault modes are discussed. The proposed measure is called expected distinguishability and is based of the previous distinguishability measure and two methods to compute expected distinguishability are presented.

  • 269.
    Jung, Daniel
    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.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Residual change detection using low-complexity sequential quantile estimation2017In: 20th IFAC World Congress / [ed] Denis Dochain, Didier Henrion, Dimitri Peaucelle, 2017, Vol. 50, p. 14064-14069, article id 1Conference paper (Refereed)
    Abstract [en]

    Detecting changes in residuals is important for fault detection and is commonly performed by thresholding the residual using, for example, a CUSUM test. However, detecting variations in the residual distribution, not causing a change of bias or increased variance, is difficult using these methods. A plug-and-play residual change detection approach is proposed based on sequential quantile estimation to detect changes in the residual cumulative density function. An advantage of the proposed algorithm is that it is non-parametric and has low computational cost and memory usage which makes it suitable for on-line implementations where computational power is limited.

  • 270.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Khorasgani, Hamed
    Inst. of Software-integrated Systems, Vanderbilt Univ., USA.
    Frisk, Erik
    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.
    Biswas, Gautam
    Inst. of Software-integrated Systems, Vanderbilt Univ., USA.
    Analysis of fault isolation assumptions when comparing model-based design approaches of diagnosis systems2015In: Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes Safeprocess'15, Elsevier, 2015, Vol. 48, no 21, p. 1289-1296Conference paper (Refereed)
    Abstract [en]

    Most model-based diagnosis approaches reported in the literature adopt a generic architecture and approach. However, the fault hypotheses generated by these methods may differ. This is not only due to the methods, but also on the basic assumptions made by different diagnostic algorithms on fault manifestation and evolution. While comparing different diagnosis approaches, the assumptions made in each case will have a significant effect on fault diagnosability performance and must therefore also be taken into consideration. Thus, to make a fair comparison, the different approaches should be designed based on the same assumptions. This paper studies the relation between a set of commonly made assumptions and fault isolability performance in order to compare different diagnosis approaches. As a case study, five developed diagnosis systems for a wind turbine benchmark problem are evaluated to analyze the type of assumptions that are applied in the different designs.

  • 271.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Ng, Kok Yew
    School of Engineering, Ulster University, Newtownabbey, UK; Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia, Malaysia.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Combining model-based diagnosis and data-driven anomaly classifiers for fault isolation2018In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 80, p. 146-156Article in journal (Refereed)
    Abstract [en]

    Machine learning can be used to automatically process sensor data and create data-driven models for prediction and classification. However, in applications such as fault diagnosis, faults are rare events and learning models for fault classification is complicated because of lack of relevant training data. This paper proposes a hybrid diagnosis system design which combines model-based residuals with incremental anomaly classifiers. The proposed method is able to identify unknown faults and also classify multiple-faults using only single-fault training data. The proposed method is verified using a physical model and data collected from an internal combustion engine.

    The full text will be freely available from 2020-09-09 11:37
  • 272.
    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.

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  • 273.
    Jung, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Yew Ng, Kok
    Monash University, Malaysia.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    A combined diagnosis system design using model-based and data-driven methods2016In: 2016 3RD CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), IEEE , 2016, p. 177-182Conference paper (Refereed)
    Abstract [en]

    A hybrid diagnosis system design is proposed that combines model-based and data-driven diagnosis methods for fault isolation. A set of residuals are used to detect if there is a fault in the system and a consistency-based fault isolation algorithm is used to compute all diagnosis candidates that can explain the triggered residuals. To improve fault isolation, diagnosis candidates are ranked by evaluating the residuals using a set of one-class support vector machines trained using data from different faults. The proposed diagnosis system design is evaluated using simulations of a model describing the air-flow in an internal combustion engine.

  • 274.
    Juto, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Driving Simulator Development and Performance Study2010Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The driving simulator is a vital tool for much of the research performed at theSwedish National Road and Transport Institute (VTI). Currently VTI posses three driving simulators, two high fidelity simulators developed and constructed by VTI, and a medium fidelity simulator from the German company Dr.-Ing. Reiner Foerst GmbH. The two high fidelity simulators run the same simulation software, developed at VTI. The medium fidelity simulator runs a proprietary simulation software. At VTI there is a wish to integrate the medium fidelity Foerst Trainer simulator hardware into the VTI simulation software environment. This would increase research, development and maintanance flexibility and simulator availability since development and research could be performed on one additional simulator. Anintegration would lead to a homogenous software environment that also decreasesdevelopment, maintanance and training costs.To integrate the Foerst Trainer simulator and the VTI simulation software to communicate a program that translates and relays input and output between the two was developed. An assessment of the hardware-software integration was performed through an experiment where the high fidelity Simulator 3 and the medium fidelity Foerst Trainer simulator were compared. The experiment was designed to measure the participants driving performances and the perceived realism of the simulator. The results of the experiment shows that there is suprisingly small differences between the simulators, but more research is needed for more conclusive results.

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  • 275.
    Karjalainen, Max
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Real-Time Estimation of Tire Stiffness2016Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A tire is an essential part on a vehicle. Different tires have different properties, and one of them is the longitudinal stiffness of the tire. Tire stiffness can be explained by modelling the tire as small thread compounds. These small thread compounds will have contact with the surface and will contain one adhesion and one sliding region. The slip is the motion of the thread compounds relative to the surface. The forces that act on the thread compounds are divided by slip and this is defined as tire stiffness.

    This thesis presents a method to estimate the tire stiffness in real-time. By using different algorithms, such as Recursive Least Squares and Least Mean Square, a good approximation of the tire stiffness can be achieved. 

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  • 276.
    Karlsson, Lina
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Sensorless Control of a Hybrid Stepper Motor2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Electrical drives are widely used in today’s society. They can be found in bothhousehold products and in the industry. One application where electrical drivesare used is in robots for mowing lawns. In the studied robots the motors in theelectrical drives used for propulsion are Brush Less Direct Current motors, BLDCmotors.The BLDC-motor has its maximum torque at high speeds and thereforea gearbox is needed. The gearbox is space consuming, add costs and consists ofmechanical parts that wear during use. Of interest is therefore to investigate ifthere are other electrical drives which can be used for propulsion.A motor who has its maximum torque at low speeds is the Stepper motor, andtherefore it is of interest to investigate if a stepper motor could replace the BLDCmotor.A drawback with the stepper motor is that it always consumes maximumcurrent and therefore a current controller is beneficial. Together with currentcontrol, speed control is needed to make the robot run at desired speed. To beable to perform an accurate current and speed control feedback from the motor isneeded. Information about the rotor angle and velocity can be used for the speedcontrol and the load angle can be used for the current control since the current isproportional to the load torque.To estimate the rotor angle and velocity a model has been developed. Themodel is based on fundamental electrical and mechanical equations and neglectsthe current and position dependence of the inductance and flux linkage. To completethe model three motor parameters, the maximum detent torque Tdm, themaximum flux linkage  m and the friction constant B was determined. Parameterdetermination was done by linear regression and by using an Extended KalmanFilter, EKF. The result of the parameter determination were Tdm = 0.2152 Nm, m = -0.002854 Vs/rad and B = 0.01186 Nms/rad.The model is used in an EKF to estimate the rotor angle and angular velocity.The result of the implemented EKF seems promising. When making the rotortake a step in velocity from 3.927 rad/s to 7.85 rad/s the EKF estimates the stateswith only a small bias: 0.02 rad for the angle, 0.3 rad/s for the velocity, 0.005 Afor phase a current and 0.0004 A for phase b current.To estimate the load angle the Sliding Discrete Fourier Transform is used. Theexpected relation between the load torque and load angle is sinusoidal. The loadangle is calculated from data where the external load is between 0-2.5 Nm. Inthat area the load angle shows the expected sinusoidal appearance and the loadangle is in the area between 0.1 and 0.45 rad. At 3 Nm the rotor stalls and it isshown that the load angle varies between 0 and 2 rad when the rotor is stalled.

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  • 277.
    Karlsson, Robin
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Parameter Estimation for a Vehicle Longitudinal Model2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    System modelling has an important role in vehicle development cycles. Hardware field tests are often replaced by simulations, especially during the preliminary design stages. Although system modelling is a time consuming task, significant amount of the overall development time and resources can be reduced if an accurate model is available.

    In order to develop a good simulation model, a sound method for parameterising the model is desired. A favourable parameter identification not only provides an accurate model, but also requires less resources both time-wise and monetarily.

    In this thesis, a model for the longitudinal dynamics of a passenger vehicle is presented. Unknown parameters in the model are estimated and the model is validated with measurements obtained experimentally. It is anticipated that the model will be used in a dynamometer, where the longitudinal forces on the vehicle are simulated and the corresponding torques are exerted on the driving wheels.

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  • 278.
    Kerai, Hiren
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Verem, Andrej
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Physically Based Models for Predicting Exhaust Temperatures in SI Engines2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    To have knowledge about the gas and material temperatures in the exhaust system of today's vehicles is of great importance. These temperatures need to be known for component protection, control- and diagnostic purposes. Today mostly map-based models are used which are not accurate enough and difficult to tune since it consist of many parameters.

    In this thesis physically based models are developed for several components in the exhaust system. The models are derived through energy balances and are more intuitive compared to the current map-based models. The developed models are parameterized and validated with measurements from wind tunnel experiments and driving scenarios on an outdoor track.

    The engine out model is modeled theoretically and is therefore not parameterized or validated. The model for the temperature drop over the exhaust manifold could not be validated due to the pulsations occurring in the exhaust manifold, however suggestions on how to solve this problem are given in this report. The models for the turbocharger, the catalyst and the downpipe are parameterized and validated with good results in this thesis. The mean absolute error for the validation data set for the turbocharger is 0.46 % and 1.01 % for the catalyst. The mean absolute percentage error for the downpipe is 1.07 %.

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    Physically Based Models for Predicting Exhaust Temperatures in SI Engines
  • 279.
    Kharrazi, Sogol
    et al.
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd and Transport Res Inst, Sweden.
    Almen, Marcus
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering. Saab Def and Space, S-58015 Linkoping, Sweden.
    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.
    Extending Behavioral Models to Generate Mission-Based Driving Cycles for Data-Driven Vehicle Development2019In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, no 2, p. 1222-1230Article in journal (Refereed)
    Abstract [en]

    Driving cycles are nowadays, to an increasing extent, used as input to model-based vehicle design and as training data for development of vehicle models and functions with machine learning algorithms. Recorded real driving data may underrepresent or even lack important characteristics, and therefore there is a need to complement driving cycles obtained from real driving data with synthetic data that exhibit various desired characteristics. In this paper, an efficient method for generation of mission-based driving cycles is developed for this purpose. It is based on available effective methods for traffic simulation and available maps to define driving missions. By comparing the traffic simulation results with real driving data, insufficiencies in the existing behavioral model in the utilized traffic simulation tool are identified. Based on these findings, four extensions to the behavioral model are suggested, staying within the same class of computational complexity so that it can still be used in a large scale. The evaluation results show significant improvements in the match between the data measured on the road and the outputs of the traffic simulation with the suggested extensions of the behavioral model. The achieved improvements can be observed with both visual inspection and objective measures. For instance, the 40% difference in the relative positive acceleration of the originally simulated driving cycle compared to real driving data was eliminated using the suggested model.

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  • 280.
    Kharrazi, Sogol
    et al.
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd and Transport Res Inst, S-58195 Linkoping, Sweden.
    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.
    Driving Behavior Categorization and Models for Generation of Mission-based Driving Cycles2019In: 2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), IEEE , 2019, p. 1349-1354Conference paper (Refereed)
    Abstract [en]

    The concept of mission-based driving cycles has been introduced as an efficient way of generating driving cycles with desired characteristics for data-driven development of vehicle powertrains. Mission-based driving cycles can be generated using traffic simulation tools with improved behavioral models that match simulation outputs and naturalistic driving data. Here, driving behavior categorization and how it can be used to create a set of differently parameterized behavioral models corresponding to various types of drivers, are studied. The focus is on curvy road driving, and two different categorization features are used, speed through the curves and the braking behavior.

  • 281.
    Kharrazi, Sogol
    et al.
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering. Swedish Natl Rd and Transport Res Inst VTI, Linkoping, Sweden.
    Nielsen, Lars
    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.
    Design cycles for a given driving mission2018In: DYNAMICS OF VEHICLES ON ROADS AND TRACKS, VOL 1, CRC PRESS-TAYLOR & FRANCIS GROUP , 2018, p. 323-328Conference paper (Refereed)
    Abstract [en]

    Representative driving cycles are of key importance for design and dimensioning of powertrains. One approach for generation of representatives driving cycles is to define relevant driving missions which include different street types, obstacles and traffic conditions, and simulate them in a traffic simulation tool. Such a simulation approach will also require representative driver models to generate the speed profiles for the defined driving missions. Feasibility of this approach is investigated in this paper.

  • 282.
    Khorasgani, Hamed
    et al.
    Hitachi Amer Ltd, CA 95054 USA.
    Biswas, Gautam
    Vanderbilt Univ, TN 37212 USA.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Structural Methodologies for Distributed Fault Detection and Isolation2019In: Applied Sciences, E-ISSN 2076-3417, Vol. 9, no 7, article id 1286Article in journal (Refereed)
    Abstract [en]

    The increasing complexity and size of cyber-physical systems (e.g., aircraft, manufacturing processes, and power generation plants) is making it hard to develop centralized diagnosers that are reliable and efficient. In addition, advances in networking technology, along with the availability of inexpensive sensors and processors, are causing a shift in focus from centralized to more distributed diagnosers. This paper develops two structural approaches for distributed fault detection and isolation. The first method uses redundant equation sets for residual generation, referred to as minimal structurally-over-determined sets, and the second is based on the original model equations. We compare the diagnosis performance of the two algorithms and clarify the pros and cons of each method. A case study is used to demonstrate the two methods, and the results are discussed together with directions for future work.

  • 283. Khorasgani, Hamed
    et al.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Structural approach for distributed fault detection and isolation2015Conference paper (Refereed)
    Abstract [en]

    This paper presents a framework for distributed fault detection and isolation in dynamic systems. Our approach uses the dynamic model of each subsystem to derive a set of independent, local diagnosers. If needed, the subsystem model is extended to include measurements and model equations from its immediate neighbors to compute its diagnosis. Our approach is designed to ensure that each subsystem diagnoser provides the correct results, therefore, a local diagnosis result is equivalent to the results that would be produced by a global system diagnoser. We discuss the distribute diagnosis algorithm, and illustrate its application using a multi-tank system.

  • 284. Khorasgani, Hamed
    et al.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Frisk, Erik
    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.
    Off-line robust residual selection using sensitivity analysis2014Conference paper (Refereed)
    Abstract [en]

    Model-based approaches to fault detection and isolation (FDI) rely on accurate models of the plant and a sufficient number of reliable measurements for residual generation and analysis. However, in realistic situations, there can be uncertainties in the plant models and measurements, which have a negative impact on the diagnosability performance that depends on the system state. In other words, the impact of the uncertainties can be larger in some operating regions as compared to others. To achieve acceptable performance in practice, it is necessary to find a set of residuals that are sufficiently sensitive to faults but robust to uncertainties across all operating conditions. In this paper, a quantitative measure, called detectability ratio, is used to evaluate and quantify detectability performance of different residuals in different operating regions. This measure is used to find a minimal residual set that fulfills a set of desired diagnosability performance requirements. The proposed method is demonstrated and validated through a case study.

  • 285.
    Khorasgani, Hamed
    et al.
    Vanderbilt University, TN 37235 USA.
    Jung, Daniel
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Biswas, Gautam
    Vanderbilt University, TN 37235 USA.
    Frisk, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Krysander, Mattias
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Robust Residual Selection for Fault Detection2014In: 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2014, p. 5764-5769Conference paper (Refereed)
    Abstract [en]

    A number of residual generation methods have been developed for robust model-based fault detection and isolation (FDI). There have also been a number of offline (i.e., design-time) methods that focus on optimizing FDI performance (e.g., trading off detection performance versus cost). However, design-time algorithms are not tuned to optimize performance for different operating regions of system behavior. To do this, would need to define online measures of sensitivity and robustness, and use them to select the best residual set online as system behavior transitions between operating regions. In this paper we develop a quantitative measure of residual performance, called the detectability ratio that applies to additive and multiplicative uncertainties when determining the best residual set in different operating regions. We discuss this methodology and demonstrate its effectiveness using a case study.

  • 286.
    Kjelldal, Therese
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    A Control System for Battery Charging in Buses2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A common configuration in buses is that the engine is placed in the rear of the bus and that the batteries are placed in thefront of the bus due to optimization of the distribution of the weight. The long wires running between the engine and the batteries together with large power consuming units, such as fans and air condition units, result in voltage drops. The voltage drops contribute to the battery charging voltage level being lower than desired.

    The aim with this thesis work is to implement a control system that increases the battery voltage level when the voltage drops occur. Measurements are performed on an articulated bus that is in focus throughout the whole thesis work. A model for the electrical circuit of the bus is created and used when investigating the stability of the control system. The control system isimplemented in the bus, where also verification tests are performed.

    The verification tests confirm that the control system raises the battery charging voltage to the desired level. The increased voltage level makes the batteries reach a higher state of charge in shorter time since the control system provides the batteries with more charge.

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  • 287.
    Klasén, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Modeling and Estimation of Long Route EGR Mass Flow in a Turbocharged Gasoline Engine2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Due to the continuous work in the automobile industry to reduce the environmental impact, reduce fuel consumption and increase efficiency, new technologies need to be developed and implemented in vehicles. For spark ignited engines, one technology that has received more attention in recent years is long route Exhaust Gas Recirculation (EGR), which means that exhaust gases after the turbine are transported back to the volume before the compressor in the air intake system of the engine. In this work, the components of the long route EGR system is modeled with mean value engine models in Simulink, and implemented in a existing Simulink engine model. Then different methods for estimating the mass flow over the long route EGR system are compared, and the transport delays for the recirculated exhaust gases in the engines air intake system are modeled. This work is based on measurements done on an engine rig, on which a long route EGR system was installed. Finally, some ideas on how a long route EGR system on a gasoline engine can be controlled are presented based on the results in this thesis work.

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  • 288.
    Klein, Inger
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Framstående utbildningsmiljö - Hur blir man det?2008In: Nätverket Ingenjörsutbildningarnas Utvecklingskonferens 2008, 2008Conference paper (Other academic)
    Abstract [sv]

    Studierektorsområdet Reglersystem vid LiTH (Tekniska Högskolan vid Linköpings universitet) tilldelades 2007 utmärkelsen Framstående Utbildningsmiljö av Högskoleverket. Utmärkelsen gavs till sammanlagt fem utbildningsmiljöer, varav två är verksamma inom ingenjörsutbildning. I detta bidrag avser vi att redogöra för denna process och de faktorer som främst bidrog till att området Reglersystem fick denna utmärkelse. De faktorer som lyfts fram som centrala för att åstadkomma en god utbildningskvalité är framför allt att ha tydliga mål för utbildningen, en gedigen ämnesmässig grund, en väl fungerande organisation och positiv attityd bland alla medverkande samt former för lärande och examination som är anpassade till utbildningens mål.

  • 289.
    Klein, Marcus
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    A specific heat ratio model and compression ratio estimation2004Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Cylinder pressure modeling and heat release analysis are today important and standard tools for engineers and researchers, when developing and tuning new engines. An accurate specific heat ratio model is important for an accurate heat release analysis, since the specific heat ratio couples the systems energy to other thermodynamic quantities.

    The objective of the first part is therefore to investigate models of the specific heat ratio for the single-zone heat release model, and find a model accurate enough to introduce a cylinder pressure modeling error less than or in the order of the cylinder pressure measurement noise, while keeping the computational complexity at a minimum. As reference, a specific heat ratio is calculated for burned and unburned gases, assuming that the unburned mixture is frozen and that the burned is at chemical equilibrium. Use of the reference model in heat release analysis is too time consuming and therefore a set of simpler models. both existing and newly developed, are compared to the reference model.

    A two-zone mean temperature model and the Vibe function are used to parameterize the mass fraction burned. The mass fraction burned is used to interpolate the specific heats for the unburned and burned mixture, and then form the specific heat ratio, which renders a small enough modeling error in γ. The impact that t his modeling error has on the cylinder pressure is less than that of the measurement noise, and fifteen times smaller than the model originally suggested in Gatowski et al. [1984]. The computational time is increased with 40 % compared to the original setting, but reduced by a factor 70 compared to precomputed tables from the full equilibrium program. The specific heats for the unburned mixture are captured within 0.2 % by linear functions, and the specific heats for the burned mixture are captured within 1 % by higher-order polynomials for the major operating range of a spark ignited (SI) engine.

    The second part is on compression ratio estimation based on measured cylinder pressure traces. Four methods for compression ratio estimation based on both motored and fired cylinder pressure traces are described and evaluated for simulated and experimental data. The first three methods rely upon a model of polytropic compression for the cylinder pressure, and it is shown that they give a good estimate of the compression ratio for simulated cycles at low compression ratios, although the estimat es are biased. The polytropic model lacks information about heat transfer and therefore, for high compression ratios, this model error causes the estimates to become more biased. The fourth method includes heat transfer, crevice effects, and a commonly used heat release model for firing cycles. This method is able to estimate the compression ratio more accurately at both low and high compression ratios. An investigation of how the methods perform when subjected to parameter deviations in crank angle phasing, cylinder pressure bias and heat transfer shows that the third and fourth method can deal with these parameter deviations.

  • 290.
    Klein, Marcus
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Eriksson, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Methods for Cylinder Pressure Based Compression Ratio Estimation2006Conference paper (Refereed)
  • 291.
    Klein, Marcus
    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.
    Utilizing Cylinder Pressure Data for Compression Ratio Estimation2005In: Proceedings of the 16th IFAC World Congress, Elsevier, 2005Conference paper (Refereed)
    Abstract [en]

    Four methods for compression ratio estimation based on cylinder pressure traces are developed and evaluated for simulated and experimental cycles. Three methods rely upon a model of polytropic compression for the cylinder pressure. It is shown that they give good estimates with a small bias at low compression ratios. A variable projection algorithm with a logarithmic norm of the cylinder pressure yields the smallest confidence intervals and shortest computational time for these three methods. This method is recommended when computational time is an important issue. The polytropic pressure model lacks information about heat transfer and therefore the estimation bias increases with compression ratio. The fourth method includes heat transfer, crevice effects, and a commonly used heat release model for firing cycles. This method estimates the compression ratio more accurately in terms of bias and variance. The method is more computationally demanding and thus recommended when estimation accuracy is the most important property. In order to estimate the compression ratio as accurately as possible, motored cycles with high initial pressure should be used.

  • 292.
    Klein, Marcus
    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.
    Utilizing Cylinder Pressure Data for Compression Ratio Estimation2005In: Proceedings of the 16th IFAC World Congress, IFAC Papers Online, 2005, Vol. 38, p. 319-324Conference paper (Refereed)
    Abstract [en]

    Four methods for compression ratio estimation based on cylinder pressure traces are developed and evaluated for simulated and experimental cycles. Three methods rely upon a model of polytropic compression for the cylinder pressure. It is shown that they give good estimates with a small bias at low compression ratios. A variable projection algorithm with a logarithmic norm of the cylinder pressure yields the smallest confidence intervals and shortest computational time for these three methods. This method is recommended when computational time is an important issue. The polytropic pressure model lacks information about heat transfer and therefore the estimation bias increases with compression ratio. The fourth method includes heat transfer, crevice effects, and a commonly used heat release model for firing cycles. This method estimates the compression ratio more accurately in terms of bias and variance. The method is more computationally demanding and thus recommended when estimation accuracy is the most important property. In order to estimate the compression ratio as accurately as possible, motored cycles with high initial pressure should be used.

  • 293.
    Klein, Marcus
    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, Faculty of Science & Engineering.
    Nilsson, Ylva
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Compression Estimation from Simulated and Measured Cylinder Pressure2003In: SAE technical paper series, ISSN 0148-7191, Vol. 111, no 3Article in journal (Refereed)
    Abstract [en]

    Three methods for estimating the compression from measured cylinder pressure traces are described and evaluated for both motored and fired cycles against simulated and measured cylinder pressure. The first two rely upon a model of polytropic compression, and it is shown that they give a good estimate of the compression ratio for simulated cycles for low compression ratios. For high compression ratios, these simple models lack the information about heat transfer. The third method includes a standard heat transfer and crevice effect model, together with a heat release model and is able to estimate the compression ratio more accurately.

  • 294.
    Klein, Marcus
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Eriksson, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Åslund, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Compression ratio estimation based on cylinder pressure data2006In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 14, no 3 SPEC. ISS., p. 197-211Article in journal (Refereed)
    Abstract [en]

    Four methods for compression ratio estimation based on cylinder pressure traces are developed and evaluated for both simulated and experimental cycles. The first three methods rely upon a model of polytropic compression for the cylinder pressure. It is shown that they give a good estimate of the compression ratio at low compression ratios, although the estimates are biased. A method based on a variable projection algorithm with a logarithmic norm of the cylinder pressure yields the smallest confidence intervals and shortest computational time for these three methods. This method is recommended when computational time is an important issue. The polytropic pressure model lacks information about heat transfer and therefore the estimation bias increases with the compression ratio. The fourth method includes heat transfer, crevice effects, and a commonly used heat release model for firing cycles. This method is able to estimate the compression ratio more accurately in terms of bias and variance. The method is more computationally demanding and is therefore recommended when estimation accuracy is the most important property. © 2005 Elsevier Ltd. All rights reserved.

  • 295.
    Klein, Markus
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Evaluating some Gain Scheduling Strategies in Diagnosis of a Tank System1999Report (Other academic)
    Abstract [en]

    In model-based diagnosis the problem of finding all the relations that can be used to detect and isolate different faults, is solved for linear systems, with e.g. “The Minimal Polynomial Basis Method”. However, for nonlinear systems the situation is much more complicated. Here an approach will be taken using the linear method above together with gain scheduling. Linear residual generators are designed at a number of stationary points. The approach is based on using a nominal selector matrix, using null-space redesign dependent on the scheduling variable, and using a proposed optimization method. Two different gain scheduling strategies are applied to form the residual generators between design points, namely nearest neighbour approximation and linear interpolation. The approach is applied to a simple nonlinear system consisting of two coupled water tanks. The simulations show that the performance of the residual generators are good under steady state conditions. It is also shown that linear interpolation has better performance than nearest neighbour approximation, especially during transients.

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    Evaluating some Gain Scheduling Strategies in Diagnosis of a Tank System
  • 296.
    Klein, Markus
    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.
    A specific heat ratio model for single-zone heat release models2004In: SAE Technical Papers 2004-01-1464, SAE International , 2004, article id 2004-01-1464Conference paper (Refereed)
    Abstract [en]

    The objective is to investigate models of the specific heat ratio for the single-zone heat release model, and find a model accurate enough to introduce a modeling error less than or in the order of the cylinder pressure measurement noise, while keeping the computational complexity at a minimum. Based on assumptions of frozen mixture for the unburned mixture and chemical equilibrium for the burned mixture, the specific heat ratio is calculated using a full equilibrium program for an unburned and a burned air-fuel mixture, and compared to already existing and newly proposed approximative models of γ.

    A two-zone mean temperature model, Matekunas pressure ratio management and the Vibe function are used to parameterize the mass fraction burned. The mass fraction burned is used to interpolate the specific heats for the unburned and burned mixture, and then form the specific heat ratio, which renders a small enough modeling error in γ. The specific heats for the unburned mixture is captured within 0.2 % by a linear function, and the specific heats for the burned mixture is captured within 1 % by a higher-order polynomial for the major operating range of a spark ignited (SI) engine.

  • 297.
    Klein, Markus
    et al.
    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.
    Evaluating some Gain Scheduling Strategies in Diagnosis of a Tank System2000In: IFAC Proceedings Volumes, IFAC Papers Online, 2000, Vol. 33, p. 879-884Conference paper (Refereed)
    Abstract [en]

    In model-based diagnosis the problem of finding all the relations that can be used to detect and isolate different faults, is solved for linear systems. However, for nonlinear systems the situation is more complicated. Here an approach will be taken using a linear method together with gain scheduling. Linear residual generators are designed at a number of stationary points. The approach is based on using a nominal selector matrix, using null-space redesign dependent on the scheduling variable, and using a proposed optimization method. Two different gain scheduling strategies are applied to form the residual generators between design points, namely nearest neighbor approximation and linear interpolation. The approach is applied to a simple nonlinear system consisting of two coupled water tanks. The simulations show that the performance of the residual generators are good under steady state conditions. It is also shown that linear interpolation has better performance than nearest neighbor approximation.

  • 298.
    Klinga, Emil
    Linköping University, Department of Electrical Engineering, Vehicular Systems.
    Modeling of the Melting Process in an AdBlue Tank2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This master thesis is covering the modeling of the melting process in a tank filled with AdBlue. Due to AdBlue freezing at temperatures below -11 degree there is a need to add heat to be able to secure dosing in all situations. A rig for simulating freezing conditions is created with the possibility to store AdBlue in temperatures down to -40 degree. Temperatures are measured in and around the tank containing AdBlue and in the equipment used for adding heat. Two models are created from physical relations to estimate the mass of AdBlue melted, a static temperature model and a dynamic temperature model. The static model shows good results when calibrated at this specific setup and is very easy to use. The dynamic temperature model is more advanced but describes the real physical system better without external calibration.

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  • 299.
    KNUTFELT, MARKUS
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Charging Cost Optimization of Plug-in Hybrid Electric Vehicles2015Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The future success of chargeable vehicles will, among other factors, depend on their charging costs and their ability to charge with minimal disturbances to the national, local and household electrical grid. To be able to minimize costs and schedule charging sessions, there has to be knowledge of how the charging power varies with time. This is called charging profile. A number of charging profiles for a Volvo V60 plug‑in hybrid electric vehicle have been recorded. For charging currents above 10 A they prove to be more complex than are assumed in most current research papers.

     

    The charging profiles are used together with historical electricity prices to calculate charging costs for 2013 and 2014. Charging is assumed to take place during the night, between 18:00 and 07:00, with the battery being totally depleted at 18:00. By using a timer to have the charging start at 01:00, instead of immediately at 18:00, annual charging costs are reduced by approximately 7 to 8%. By using dynamic programming to optimize the charging sessions, annual charging costs are reduced by approximately 10 to 11%. An interesting issue regarding dynamic programming was identified, namely when using a limited set of predetermined discrete control signals, interpolation returns unrealizable cost-to-go values. This occurs specifically for instances crossing the zero cost-to-go area boundary.

     

    It is concluded that the mentioned savings are realizable, via implementing timers or optimization algorithms into consumer charging stations. Finally, by using these decentralized charging planning tools and seen from a power usage perspective, at least 30% of the Swedish vehicle fleet could be chargeable and powered by the electrical grid.

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  • 300.
    Koschorrek, Philipp
    et al.
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Piccini, Tommaso
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Öberg, Per
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Mester, Rudolf
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology. University of Frankfurt, Germany.
    A multi-sensor traffic scene dataset with omnidirectional video2013In: 2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), IEEE conference proceedings, 2013, p. 727-734Conference paper (Refereed)
    Abstract [en]

    The development of vehicles that perceive their environment, in particular those using computer vision, indispensably requires large databases of sensor recordings obtained from real cars driven in realistic traffic situations. These datasets should be time shaped for enabling synchronization of sensor data from different sources. Furthermore, full surround environment perception requires high frame rates of synchronized omnidirectional video data to prevent information loss at any speeds.

    This paper describes an experimental setup and software environment for recording such synchronized multi-sensor data streams and storing them in a new open source format. The dataset consists of sequences recorded in various environments from a car equipped with an omnidirectional multi-camera, height sensors, an IMU, a velocity sensor, and a GPS. The software environment for reading these data sets will be provided to the public, together with a collection of long multi-sensor and multi-camera data streams stored in the developed format.

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