Applying an Extended Flamelet Model for a Multiple Injection Operating Strategy in a Common-Rail DI Diesel Engine

Gauding, Michael; Felsch, C.; Kerschgens, Bruno; Vanegas, A.; Won, Hyun Woo; Peters, N.; Hasse, Christian

doi:10.4271/2009-01-0720

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…The reduced mechanism for the IDEA fuel was coupled with a representative interactive flamelet (RIF) model to simulate the combustion of a direct-injection diesel engine. The results indicated that the in-cylinder pressure, heat release rate and emissions were well reproduced by the model [21,22].…”

Section: Introductionmentioning

confidence: 77%

Development of a skeletal mechanism for diesel surrogate fuel by using a decoupling methodology

Chang

Jia

et al. 2015

Combustion and Flame

169

100

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Section: Introductionmentioning

confidence: 77%

Development of a skeletal mechanism for diesel surrogate fuel by using a decoupling methodology

Chang

Jia

et al. 2015

Combustion and Flame

169

100

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“…16,17 In addition to the injection timing, the amount of fuel sprayed in the pilot injection has also been reported to be effective on performance and emissions. 12,18,19 The main purpose of early post injection is to improve the late stage mixing and consequently reduce smoke, 15 soot, 20,21 and PM emissions. 22 Late post injection also assists the aftertreatment system.…”

Section: Introductionmentioning

confidence: 99%

“…The main purpose of early post injection is to improve the late stage mixing and consequently reduce smoke, 15 soot, 20,21 and PM emissions. 22 Late post injection also assists the aftertreatment system.…”

Section: Introductionmentioning

confidence: 99%

Development of optimal diesel injection strategy based on the prediction of performance and emissions using deep neural network

Güner

Kaleli

Bakırcı

et al. 2021

International Journal of Engine Research

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This study aims to determine the optimal injection strategy by predicting the performance and exhaust emission parameters of a four-cylinder CRDI engine under several operating conditions. The experimental determination procedure is challenging and expensive calibration task since it requires a high number of tests. Many studies have focused on a limited level of parameters. In this study, design of experiments technique and deep neural network (DNN) modeling are used together. The experimental data set for the model is created using Taguchi L16 and L32 orthogonal arrays. The DNN model is developed to predict [Formula: see text], [Formula: see text], HC, and CO emissions with speed, torque, injection timings and fuel quantities of each injection called as pilot1, pilot2, main, and post. In this way, it has become possible to evaluate the effects of a larger number of operating parameters in a wide range than the literature. The developed DNN model predicts the [Formula: see text], [Formula: see text], HC, and CO with R2 0.939, 0.943, 0.963, and 0.966, respectively. Additionally, RMSE and MAE values for the model are between 0.024 and 0.048. The proposed method compared with the conventional look-up table method performs better in reducing the complexity and cost of experiments and exploration of the effects of injection parameters on engine emission and performance characteristics in a wide engine operating range. In conclusion, until 2300 rpm at specified torque (90 Nm), it is found that 70% of fuel quantity should inject in main injection to minimize [Formula: see text] and [Formula: see text] emissions. The post injection quantity should be increased by reducing the amount of main injection from this operating condition on. Furthermore, it is observed that the ratios of pilot injection durations do not change with increasing engine speed, but quantity of first pilot injection is more than that of second pilot injection.

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Prediction of non-premixed combustion regimes in direct injection compression ignition engines

Niemietz,

Denker,

Gauding

et al. 2024

Proceedings of the Combustion Institute

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Applying an Extended Flamelet Model for a Multiple Injection Operating Strategy in a Common-Rail DI Diesel Engine

Cited by 6 publications

References 30 publications

Development of a skeletal mechanism for diesel surrogate fuel by using a decoupling methodology

Development of a skeletal mechanism for diesel surrogate fuel by using a decoupling methodology

Development of optimal diesel injection strategy based on the prediction of performance and emissions using deep neural network

Prediction of non-premixed combustion regimes in direct injection compression ignition engines

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