An Easily Tunable Wall-Wetting Model for PFI Engines

Locatelli, Marzio; Onder, Christopher H.; Geering, Hans P.

doi:10.4271/2004-01-1461

Cited by 12 publications

(21 citation statements)

References 12 publications

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“…One possibility is to represent it by a cylindric ring of fuel around the intake valve with thickness 8th and height h p as proposed in [110]. The height is the actual state variable of the wall film, whereas the thickness is a parameter which is slowly varying depending on the wall temperature.…”

Section: Wall Film Evaporationmentioning

confidence: 99%

“…In the following , a model proposed in [110], that is based on thermodynamic analogies, is presented. This model will be shown to have the same model structure as the model described by (2.65) and (2.66) while requiring much less experimental effort for the identification of the full set of parameters.…”

Section: First-principle Modelsmentioning

confidence: 99%

“…In [110], an exponential decay for the number of airborne droplets is introduced. It is assumed that all the fuel is injected instantaneously and that all droplets are identical at the beginning.…”

Section: Droplet Evaporationmentioning

confidence: 99%

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Introduction to Modeling and Control of Internal Combustion Engine Systems

Guzzella

Onder

2004

Self Cite

710

589

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SoftcOVel: reprint of the hardcover 1st edition 2004 The use of general descriptive names, registered names trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Preface Who should read this text?This text is intended for students interested in the design of classical and novel IC engine control systems. Its focus lies on the control-oriented mathematical description of the physical processes involved and on the model-based control system design and optimization. This text has evolved from a lecture series held during the last several years in the mechanical engineering (ME) department at ETH Zurich. The presumed audience is graduate ME students with a thorough understanding of basic thermodynamic and fluid dynamics processes in internal combustion engines (ICE). Other prerequisites are knowledge of general ME topics (calculus, mechanics, etc.) and a first course in control systems. Students with little preparation in basic ICE modeling and design are referred to [52] Why has this text been written?Internal combustion engines represent one of the most important technological success stories in the last 100 years. These systems have become the most frequently used sources of propulsion energy in passenger cars. One of the main reasons that this has occurred is the very high energy density of liquid hydrocarbon fuels. As long as fossil fuel resources are used to fuel cars, there are no foreseeable alternatives that offer the same benefits in terms of cost, safety, pollutant emission and fuel economy (always in a total cycle, or "wellto-wheel" sense, see e.g., [5] and [55]).Internal combustion engines still have a substantial potential for improvements; Diesel (compression ignition) engines can be made much cleaner and Otto (spark ignition) engines still can be made much more fuel efficient. Each goal can be achieved only with the help of control systems. Moreover, with the systems becoming increasingly complex, systematic and efficient system VI Preface design procedures have become technological and commercial necessities. This text addresses these issues by offering an introduction to model-based control system design for ICE. What can be learned from this text?The primary emphasis is put on the ICE (torque production, pollutant formation, etc.) and its auxiliary devices (air-charge control, mixture formation, pollutant abatement systems, etc.). Mathematical models for some of these processes will be developed below. Using these models, selected feedforward and feedback control problems will then be discussed.A model-based approach is chosen because, even though more cumbersome in the beginning, it after proves to be the most cost-effective in the long run. Especially the control system development and calibration processes benefit greatly from mathematical models at early project stages.The appendix contains a brief summary of the most important control...

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Section: Wall Film Evaporationmentioning

confidence: 99%

Section: First-principle Modelsmentioning

confidence: 99%

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Introduction to Modeling and Control of Internal Combustion Engine Systems

Guzzella

Onder

2004

Self Cite

710

589

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“…Further a strong dependence of parameters on operating conditions, which can vary rapidly during real vehicle driving, is another complicating factor. A promising direction to address these challenges is the use of physics-based models, such as in [14], [12], [13] wherein constant or slowly varying parameters (which can be different from conventional parameters in Aquino's model) are estimated on-line.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous modifications and enhancements of this model, including its adoption for individual cylinder injections, have formed the basis of production strategies. Off-line and on-line system identification/parameter estimation techniques have been used in [6], [7], [8], [16], [11], [3], [21], [22], [24], [17], [12], [2] to identify parameters in transient fuel models; the inverses of such models then yield transient fuel compensators. Applying offline/on-line system identification techniques can be intricate due to several reasons.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Equations Based Experiment Design and Adaptive Compensation of Transient Fuel Dynamics in Port-Fuel Injection Engines

Song

Kolmanovsky

Gibson

2007

2007 IEEE International Conference on Control Applications

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In this paper we consider and address two topics relevant to calibration of parameters in transient fuel compensation algorithms. The first topic concerns the optimal selection of transient trajectories over which data are collected and identification of parameters in transient fuel model, the inverse of which constitutes a transient fuel compensation algorithm, is performed. We show that this problem can be formulated as an optimal control problem, and that this optimal control problem can be solved numerically. Even with the optimal transient trajectories, our results highlight a difficulty in identifying parameters in a transient fuel model if parameters in the model of exhaust gas mixing and in the model of the Universal Exhaust Gas Oxygen (UEGO) sensor are uncertain. The second topic addresses this difficulty through the use of adaptation to adjust parameters in a transient fuel compensation algorithm, until the deviation of measured fuel-to-air ratio from the commanded fuel-to-air ratio is sufficiently reduced. Our adaptation approach is shown to be robust to uncertainties in UEGO sensor and exhaust mixing dynamics. The theme common to both developments is the use of differential sensitivity equations.

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References

2014

Modeling and Control of Engines and Drivelines

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An Easily Tunable Wall-Wetting Model for PFI Engines

Cited by 12 publications

References 12 publications

Introduction to Modeling and Control of Internal Combustion Engine Systems

Introduction to Modeling and Control of Internal Combustion Engine Systems

Sensitivity Equations Based Experiment Design and Adaptive Compensation of Transient Fuel Dynamics in Port-Fuel Injection Engines

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