Engine Control Optimization Via Nonlinear Programming

Rao, H. Suresh; Cohen, Arthur I.; Tennant, J. A.; Voorhies, K. L. Van

doi:10.4271/790177

Cited by 19 publications

(14 citation statements)

References 12 publications

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“…3 This can be accomplished using a purely experimental, or a partially model-based, approach [127], [165]. In both cases, the iterations can be performed using heuristics based on experience with previous engine calibration tasks or using systematic approaches, e.g., forming the gradients of the cost function (4.6) and using these vectors in a steepest-descent algorithm as discussed in [140], [91], [148] and [149].…”

Section: Engine Calibrationmentioning

confidence: 99%

Introduction to Modeling and Control of Internal Combustion Engine Systems

2004

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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: Engine Calibrationmentioning

confidence: 99%

Introduction to Modeling and Control of Internal Combustion Engine Systems

2004

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“…Then the calculation of J = λ T y and the updates (6)- (8) are made in the vectorized form which can be efficiently and rapidly 4 handled by MATLAB [9]. The user is provided with several options to trade-off available RAM versus the speed of computations.…”

Section: Implementation Of Dynamic Programmingmentioning

confidence: 99%

“…For conventional powertrain systems, such assessment can be successfully carried out with quasistatic optimization [1][2][3][4][5][6], which ignored the dynamics and focused on the static relations of the performance to control variables and design parameters. When the dynamics are dominant, such as for the engine cold start problem, dynamic optimization is still manageable when the time horizon is short [7,8].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Software Environment For Powertrain Feasibility Assessment Using Optimization And Optimal Control

Kolmanovsky

Sun

Sivashankar

2008

Asian Journal of Control

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With the increase in automotive powertrain complexity, an upfront assessment of powertrain capability in meeting its design targets is important early on in the development programs. The optimization of control policy based on powertrain simulation models can facilitate this assessment and establish limits of achievable performance for a given powertrain configuration and parameters. The paper discusses several computational optimization and user interface solutions for deploying a numerical optimal control approach in a user-friendly software environment.

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“…A common approach is to approximate a given dynamic vehicle driving cycle as a limited number of steady-state engine operating points, and to calibrate set points in these operating points with respect to engineering targets for the complete cycle. Early work based on this approach for gasoline engine applications can be found in Rao, Cohen, Tennant, and Van Voorhies (1979), Rishavy, Hamilton, Ayers, and Keane (1977) and early work for diesel engine applications in Schmitz, Oligschläger, and Eifles (1994). An advantage with this approach is that optimal set points for steady-state engine operation can be calculated from the engine speed and the injected fuel amount only.…”

Section: Introductionmentioning

confidence: 99%

Model-based diesel Engine Management System optimization for transient engine operation

Grahn

Johansson

McKelvey

2014

Control Engineering Practice

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Citation for the published paper: Grahn, M. ; Johansson, K. ; McKelvey, T. (2014) "Model-based diesel Engine Management System optimization for transient engine operation". Control Engineering Practice, vol. 29 pp. 103-114.http://dx. a b s t r a c tA recently developed strategy to calculate set points for controllable diesel engine systems is described, further developed, and evaluated. The strategy calculates set points with an aim to minimize fuel consumption for a given dynamic vehicle driving cycle, while keeping accumulated emissions below given limits. The strategy is based on existing methodology for steady-state engine operation, but extended to handle transient effects in the engine caused by dynamics in the engine air system. Using the strategy, set points for the complete operating range of the engine can be calculated off-line and stored in an Engine Management System, hence set points can be derived for any (steady-state or transient) driving scenario. The strategy has been evaluated using a simulation model of a complete diesel engine vehicle system. The model estimates fuel consumption, NO X , and soot emissions for a dynamic vehicle driving cycle depending on set points for boost pressure, oxygen fraction in the intake manifold, and injection timing, throughout the simulation. Using this simulation model, the strategy has been shown to decrease fuel consumption for the New European Driving Cycle with 0.56%, the Federal Test Procedure with 1.04%, and the Japanese JC08 cycle with 0.84% compared to a strategy based on steady-state engine operation.

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Engine Control Optimization Via Nonlinear Programming

Cited by 19 publications

References 12 publications

Introduction to Modeling and Control of Internal Combustion Engine Systems

Introduction to Modeling and Control of Internal Combustion Engine Systems

An Integrated Software Environment For Powertrain Feasibility Assessment Using Optimization And Optimal Control

Model-based diesel Engine Management System optimization for transient engine operation

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