Abstract Recent trends in gasoline engines, such as downsizing, downspeeding and the increase of the compression ratio make knocking combustions a serious limiting factor for engine performance. A detailed analysis of knocking events can help improving the engine performance and diagnostic strategies. An effective way is to use advanced 3D Computational Fluid Dynamics (CFD) simulation for the analysis and prediction of the combustion process. The effects of Cycle to Cycle Variation (CCV) on knocking combustions are taken into account, maintaining a \RANS\ (Reynolds Averaged Navier-Stokes) \CFD\ approach, while representing a complex running condition, where knock intensity changes from cycle to cycle. The focus of the numerical methodology is the statistical evaluation of the local air-to-fuel and turbulence distribution at the spark plugs and their correlation with the variability of the initial stages of combustion. \CFD\ simulations have been used to reproduce knock effect on the cylinder pressure trace. For this purpose, the \CFD\ model has been validated, proving its ability to predict the combustion evolution with respect to \SA\ variations, from non-knocking up to heavy knocking conditions. The pressure traces simulated by the \CFD\ model are then used to evaluate cylinder pressure-based knock indexes. Since the model is able to output other knock intensity tracers, such as the mass of fuel burned in knocking mode, or the local heat transferred to the piston, knock indexes based on the cylinder pressure trace can be related to parameters only available in a simulation environment, that are likely to be more representative of the actual knock intensity, with respect to the local pressure trace for the sensor position. The possibility of simulating hundredths of engine cycle allows using the methodology to compare the indexes quality (correlation with actual knock intensity) on a statistical base.

Comparison of Knock Indexes Based on \CFD\ Analysis

CORTI, ENRICO;FORTE, CLAUDIO;CAZZOLI, GIULIO;MORO, DAVIDE;FALFARI, STEFANIA;RAVAGLIOLI, VITTORIO
2016

Abstract

Abstract Recent trends in gasoline engines, such as downsizing, downspeeding and the increase of the compression ratio make knocking combustions a serious limiting factor for engine performance. A detailed analysis of knocking events can help improving the engine performance and diagnostic strategies. An effective way is to use advanced 3D Computational Fluid Dynamics (CFD) simulation for the analysis and prediction of the combustion process. The effects of Cycle to Cycle Variation (CCV) on knocking combustions are taken into account, maintaining a \RANS\ (Reynolds Averaged Navier-Stokes) \CFD\ approach, while representing a complex running condition, where knock intensity changes from cycle to cycle. The focus of the numerical methodology is the statistical evaluation of the local air-to-fuel and turbulence distribution at the spark plugs and their correlation with the variability of the initial stages of combustion. \CFD\ simulations have been used to reproduce knock effect on the cylinder pressure trace. For this purpose, the \CFD\ model has been validated, proving its ability to predict the combustion evolution with respect to \SA\ variations, from non-knocking up to heavy knocking conditions. The pressure traces simulated by the \CFD\ model are then used to evaluate cylinder pressure-based knock indexes. Since the model is able to output other knock intensity tracers, such as the mass of fuel burned in knocking mode, or the local heat transferred to the piston, knock indexes based on the cylinder pressure trace can be related to parameters only available in a simulation environment, that are likely to be more representative of the actual knock intensity, with respect to the local pressure trace for the sensor position. The possibility of simulating hundredths of engine cycle allows using the methodology to compare the indexes quality (correlation with actual knock intensity) on a statistical base.
Corti, Enrico; Forte, Claudio; Cazzoli, Giulio; Moro, Davide; Falfari, Stefania; Ravaglioli, Vittorio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/583233
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