liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Eriksson, Lars
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Wahlström, Johan
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Klein, Marcus
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Physical Modeling of Turbocharged Engines and Parameter Identification2009In: Automotive Model Predictive Control: Models, Methods and Applications, Springer Verlag , 2009, 1, p. 53-71Chapter in book (Refereed)
    Abstract [en]

    The common theme in this chapter is physical modeling of engines and the subjects touch three topics in nonlinear engine models and parameter identification. First, a modeling methodology is described. It focuses on the gas and energy flows in engines and covers turbocharged engines. Examples are given where the methodology has been successfully applied, covering naturally aspirated engines and both single and dual stage turbocharged engines. Second, the modeling with the emphasis on models for EGR/VGT equipped diesel engine. The aim is to describe models that capture the essential dynamics and nonlinear behaviors and that are relatively small so that they can be utilized in model predictive control algorithms. Special emphasis is on the selection of the states. The third and last topic is related to parameter identification in gray-box models. A common issue is that parameters with physical interpretation often receive values that lie outside their admissible range during the identification. Regularization is discussed as a solution and methods for choosing the regularization parameter are described and highlighted.

  • 2.
    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.

  • 3.
    Klein, Marcus
    et al.
    Linköping University, Department of Electrical Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering.
    A comparison of specific heat ratio models for cylinder pressure modeling2004Conference paper (Refereed)
  • 4.
    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)
  • 5.
    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.

  • 6.
    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.

  • 7.
    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.

  • 8.
    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.

  • 9.
    Klein, Marcus
    et al.
    Linköping University, Department of Electrical Engineering.
    Eriksson, Lars
    Linköping University, Department of Electrical Engineering.
    Åslund, Jan Olof
    Linköping University, Department of Mathematics.
    Compression ratio estimation based on cylinder pressure data2004Conference paper (Refereed)
  • 10.
    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.

  • 11.
    Klein, Markus
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Single-Zone Cylinder Pressure Modeling and Estimation for Heat Release Analysis of SI Engines2007Doctoral 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. Being able to accurately model and extract information from the cylinder pressure is important for the interpretation and validity of the result.

    The first part of the thesis treats single-zone cylinder pressure modeling, where the specific heat ratio model constitutes a key part. This model component is therefore investigated more thoroughly. For the purpose of reference, the specific heat ratio is calculated for burned and unburned gases, assuming that the unburned mixture is frozen and that the burned mixture 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 to form the specific heat ratio, which renders a cylinder pressure modeling error in the same order as 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.

    In the second part, four methods for compression ratio estimation based on cylinder pressure traces are developed and evaluated for both simulated and experimental cycles. 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 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 as high initial pressure as possible should be used.

    The objective in part 3 is to develop an estimation tool for heat release analysis that is accurate, systematic and efficient. Two methods that incorporate prior knowledge of the parameter nominal value and uncertainty in a systematic manner are presented and evaluated. Method 1 is based on using a singular value decomposition of the estimated hessian, to reduce the number of estimated parameters one-by-one. Then the suggested number of parameters to use is found as the one minimizing the Akaike final prediction error. Method 2 uses a regularization technique to include the prior knowledge in the criterion function.

    Method 2 gives more accurate estimates than method 1. For method 2, prior knowledge with individually set parameter uncertainties yields more accurate and robust estimates. Once a choice of parameter uncertainty has been done, no user interaction is needed. Method 2 is then formulated for three different versions, which differ in how they determine how strong the regularization should be. The quickest version is based on ad-hoc tuning and should be used when computational time is important. Another version is more accurate and flexible to changing operating conditions, but is more computationally demanding.

  • 12.
    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.

  • 13.
    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.

1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf