Multi-zone combustion modeling for the prediction of diesel engine cycles and engine performance parameters

Şahin, Zehra; Durgun, Orhan

doi:10.1016/j.applthermaleng.2008.01.002

Cited by 32 publications

(25 citation statements)

References 2 publications

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“…The main advantage of multi-zone models over computational fluid dynamics (CFD) tools is that more detailed chemical mechanisms can be applied directly. Therefore multi-zone modeling has been applied extensively in engine community [8][9][10][11][12][13][14][15][16]. In those studies, the complex flow phenomena are ignored.…”

Section: Introductionmentioning

confidence: 99%

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

Egüz

Maes

Leermakers

et al. 2013

Int.J Automot. Technol.

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Premixed charge compression ignition (PCCI) is a clean and efficient alternative for classical diesel combustion. The concept of PCCI combustion is associated with early injection of the fuel whilst applying high exhaust gas recirculation (EGR) levels and operation with a highly lean mixture such that ignition takes place (well) after the injection event. Thus, it is possible to reduce soot and oxides of nitrogen (NO x ) emissions simultaneously. PCCI combustion is analyzed using a multi-zone model. In the multi-zone model, chemical mechanisms which are much more detailed compared to those used in computational fluid dynamics (CFD) approaches can be introduced directly. The CFD model is still used to predict the initial fuel stratification in the cylinder which is important to improve the quality of the model. For the analysis, dedicated experiments with n-heptane are used to evaluate the results of the model. In such a multi-zone model, 10 zones prove to be sufficient to describe the stratification with adequate resolution. It is observed that different fuel distributions have a large influence on the emissions when there is no mixing between the zones. To overcome this dependence, a basic inter-zonal diffusive 2 mixing is applied. The level of mixing is estimated with a sensitivity study. When the inter-zonal mixing is included, emission results become much less sensitive to the crank angle (CA) at which the charge stratification is sampled and the simulation is initialized.

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Section: Introductionmentioning

confidence: 99%

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

Egüz

Maes

Leermakers

et al. 2013

Int.J Automot. Technol.

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“…Analiza wpływu zmian konstrukcyjnych silnika lub zmian organizacji procesu roboczego na parametry procesu spalania wymaga zastosowania modeli wielowymiarowych i wielostrefowych [10]. Należy jednak pamiętać, że zastosowanie modeli zjawisk zachodzących w przestrzeni cylindrowej silnika wymaga każdorazowej walidacji do konkretnej postaci konstrukcyjnej silnika.…”

Section: Model Procesu Spalania W Cylindrach Silnikaunclassified

Model of the combustion process in the marine 4-stroke diesel engine

Kowalski¹

2015

Mechanik

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MODEL OF THE COMBUSTION PROCESS IN THE MARINE 4-STROKE DIESEL ENGINE SUMMARY Manuscript presents a model of the combustion process in marine four-stroke diesel engine to determine the nitric oxides fraction (NOx) in the exhaust gas. This is iterative, 3-dimensional model, built on geometric mesh of the engine cylinder chamber. The model includes mathematical description of fuel injection, spray, evaporation and auto ignition and flame propagation in the cylinder. In order to determine the NOx fraction, the heat exchange phenomena description between structural elements of the cylinder has been done. The input data and boundary conditions are collected from the direct measurements. The model has been successfully validated based on the characteristics of the in-cylinder combustion pressure and NOx and oxygen fractions in the exhaust gas for all considered loads of the engine.

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“…First group is phenomenological models which are classified to single zone, two zone and multi-zone models [2,3]. In phenomenological models, thermodynamic equations are solved during engine cycle.…”

Section: Introductionmentioning

confidence: 99%

Prediction of a diesel engine exhaust gases physical properties with artificial neural network

Ghiasi

Ettefagh

Sadeghi

et al. 2014

2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings

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In recent years, ANN (artificial neural network) method has been used as an effective method for analyses of the characteristic parameters in internal combustion engines. Also, determination of the best network structure is an important part of the research work in this branch. So, this subject is the main idea of the current study. The most reliable network structure has been determined for prediction of two important engine after-treatment parameters. These parameters are pressure and temperature of the gases at EVO (exhaust valve opening) time. Outputs of four ANN models have been compared with the results of a reliable developed multi-zone combustion model. The ANN models, which have been considered in this research work, are MLP (Multi Layer Perception), RBF (Radial Basis Function), SOM (Self Organized Map) and GFF (Generalized Feed Forward) with training algorithms of LM (Levenberg Marquart)and MOM (Momentum), respectively. Finally, the MLP-LM model has been proposed as the most appropriate model. Keywords-diesel engine; multi-zone combustion model; aftertreatment; artificial neural networkI.

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Multi-zone combustion modeling for the prediction of diesel engine cycles and engine performance parameters

Cited by 32 publications

References 2 publications

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

Model of the combustion process in the marine 4-stroke diesel engine

Prediction of a diesel engine exhaust gases physical properties with artificial neural network

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