Quasi-dimensional and Empirical Modeling of Compression-Ignition Engine Combustion and Emissions

Grill, Michael; Bargende, Michael; Rether, Dominik; Schmid, Andreas

doi:10.4271/2010-01-0151

Cited by 19 publications

(8 citation statements)

References 9 publications

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“…Hence, premixed combustion was assumed for the pilot fuel. 36 A simple heat release model, such as the Wiebe model 13 (equation (A22) in the supplemental material), was used to predict the burnt mass fraction of the pilot injected fuel at the start of main combustion, 37–39 when the main injection starts before the end of the pilot combustion. When the main injection starts after the end of pilot combustion, the pilot fuel is assumed to be burnt completely before the main injection occurs.…”

Section: Methodology For Ignition Delay Predictionmentioning

confidence: 99%

Transient prediction capabilities of a novel physics-based ignition delay model in multi-pulsed direct injection diesel engines

Samuel

Ramesh

2019

International Journal of Engine Research

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This work is an extension of a novel physics-based ignition delay modeling methodology previously developed by the authors to predict physical and chemical ignition delays of multiple injections during steady operations in diesel engines. The modeling methodology is refined in this work to consider the influence of additional operating parameters such as volumetric efficiency, exhaust temperature and pressure on the ignition delay of multiple injections. Computational fluid dynamics predictions on two different engines indicated that the main spray encounters local temperatures about 60 K above average temperatures for about 1 mg of pilot. Hence, the modeling methodology was further refined to include this effect by considering the air mass trapped in pilot spray, computed based on the spray penetration and cone angle and tuned using results of the computational fluid dynamics studies. Comparisons of the ignition delay predictions with the stock boost temperature sensor and a specially incorporated, transient-capable fine wire thermocouple indicated that the measurements with stock sensor could be satisfactorily used for transients. Cycle-by-cycle changes in ignition delay could be predicted accurately when transients were imposed in boost pressure, rail pressure and main injection quantity in a turbocharged intercooled diesel engine controlled with an open engine control unit. Further validations were done even under a transient cycle when the engine was controlled by its stock engine control unit. The same tuning constants could be used for the prediction of the ignition delay under transients on another naturally aspirated engine. This indicates the suitability of the model for application in different engines. Finally, the model was incorporated within an open engine controller, and cycle-by-cycle prediction of ignition delays of the pilot and main injections were done in real time. It was possible to compute the ignition delays in less than 2 ms within engine control unit using the already available sensor inputs within an error band of ±60 µs.

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Section: Methodology For Ignition Delay Predictionmentioning

confidence: 99%

Transient prediction capabilities of a novel physics-based ignition delay model in multi-pulsed direct injection diesel engines

Samuel

Ramesh

2019

International Journal of Engine Research

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“…Several quasi-dimensional models have been developed since the early 1980s to study both gasoline and diesel engines (see, e.g., [1][2][3][4][5][6][7][8][9][10][11]) with varying degrees of fidelity. With few exceptions (e.g., [1,6,10]), however, these studies do not discuss the wall-clock time required for the computation of an engine cycle (a single compression and expansion stroke).…”

Section: Introductionmentioning

confidence: 99%

Development of a Reduced-Order Design/Optimization Tool for Automotive Engines Using Massively Parallel Computing

Aithal

Wild

2015

SAE Technical Paper Series

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Design and optimization of automotive engines present unique challenges on account of the large design space and conflicting constraints. A notable example of such a problem is optimizing the fuel consumption and reducing emissions over the drive cycle of an automotive engine. There are over twenty design variables (including operating conditions and geometry) for the abovementioned problem. Conducting design, analyses, and optimization studies over such a large parametric space presents a serious computational challenge. The large design parameter space precludes the use of detailed numerical or experimental investigations. Physics-based reduced-order models can be used effectively in the design and optimization of such problems. Since a typical drive cycle is represented by 1500 to 2000 sample data points (engine cycles), it is essential to develop fast and robust computations so that the entire engine cycle computation is done close to real-time speeds (on the order of 100-150 milliseconds). Harnessing the power of high-performance computing, it is possible to perform optimization of automotive drive cycles using massively parallel computations. In this work, we discuss the development of a parallel fast and robust reduced-order modeling tool to compute integrated quantities such as fuel consumption and emissions (NO and CO) over a range of engine drive cycles. As an illustrative example, we perform a massively parallel simulation consisting of 4096 synthetic drive cycles, representative of a fleet of cars. The impact of parameters such as humidity, initial cylinder pressure, inlet air temperature, and residual gas fraction on the performance and emission are presented.

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“…Development of such quasi-dimensional modeling tools can greatly aid the design, analysis, and optimization of IC engines. Several quasi-dimensional models have been developed since the early 1980s to study both gasoline and diesel engines (see, for example, [1][2][3][4][5][6][7][8]) with varying degrees of fidelity. With few exceptions (for instance, [3] and [7]), however, these studies do not discuss the wall-clock time required for the computation of an engine cycle (a single compression and expansion stroke).…”

Section: Introductionmentioning

confidence: 99%

“…Several quasi-dimensional models have been developed since the early 1980s to study both gasoline and diesel engines (see, for example, [1][2][3][4][5][6][7][8]) with varying degrees of fidelity. With few exceptions (for instance, [3] and [7]), however, these studies do not discuss the wall-clock time required for the computation of an engine cycle (a single compression and expansion stroke). The level of fidelity in the quasi-dimensional model and the wall-clock time required for the computation of an engine cycle are important considerations, especially for real-time optimization and control, which require the computational time to be on the order of an engine cycle (typically, 25-50 milliseconds).…”

Section: Introductionmentioning

confidence: 99%

Development of a Fast, Robust Numerical Tool for the Design, Optimization, and Control of IC Engines

Aithal

Wild

2013

SAE Technical Paper Series

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This paper discusses the development of an integrated tool for the design, optimization, and real-time control of engines from a performance and emissions standpoint. Our objectives are threefold: (1) develop a tool that computes the engine performance and emissions on the order of a typical engine cycle (25-50 milliseconds); (2) enable the use of the tool for a wide variety of engine geometries, operating conditions, and fuels with minimal user changes; and (3) couple the engine module to an efficient optimization module to enable real-time control and optimization. The design tool consists of two coupled modules: an engine module and an optimization module. The engine module consists of three components: a two-zone quasi-dimensional engine model to compute the temporal variation of temperature and pressure during the compression and power stroke, a thermal model to compute the cyclic variation of the engine wall temperature, and a reaction-rate-controlled emission model to compute engine-out NO and CO. The optimization solver is an extension of the model-based, derivative-free POUNDER and is designed to limit the number of engine model evaluations. The outputs of the engine model, thermal model, and emissions model can be used for optimizations under various design constraints. By more thoroughly using the output from the simulations, our optimization scheme reduces the number of simulation evaluations by two orders of magnitude compared with parameter sweeps and one order of magnitude compared with the standard black-box optimizer in MATLAB. These results highlight the proposed tool's potential for use in design, optimization, and real-time control of engines.

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Quasi-dimensional and Empirical Modeling of Compression-Ignition Engine Combustion and Emissions

Cited by 19 publications

References 9 publications

Transient prediction capabilities of a novel physics-based ignition delay model in multi-pulsed direct injection diesel engines

Transient prediction capabilities of a novel physics-based ignition delay model in multi-pulsed direct injection diesel engines

Development of a Reduced-Order Design/Optimization Tool for Automotive Engines Using Massively Parallel Computing

Development of a Fast, Robust Numerical Tool for the Design, Optimization, and Control of IC Engines

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