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Estimation of Turbulence Level in Spark Ignition Engine Using Experimental Data of In-Cylinder Pressure
F2018/F2018-PTE-122

Authors

Momir Sjeric
University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Croatia

Darko Kozarac, Mateo Jakoubek

Abstract

The objective of this study was to analyze the applicability of the proposed procedure for the estimation of in-cylinder turbulence level in SI engine from measured pressure data and to use it for the calibration of cycle simulation model constants. In the Laboratory of IC Engines and Vehicles at the Faculty of Mechanical Engineering and Naval Architecture in Zagreb, Croatia, the experimental setup of single cylinder IC engine was built and experimental results were used for the analysis in this study. An offline in-house code for the calculation of heat release rate from the measured in-cylinder pressure profiles was applied over different engine speeds at full load conditions. By means of the additionally developed code the estimation of turbulence intensity was made. The estimated values of turbulence intensity have been used for the calibration of 0-D turbulence model. The estimated levels of in-cylinder turbulence over analyzed operating conditions were compared with levels of in-cylinder turbulence intensity at top dead center calculated by means of the mean piston speed. The constants of cycle simulation with the quasidimensional combustion sub-model were calibrated and the simulation results of turbulence and combustion are compared with the reference and measured data. The average difference between the estimated and simulated turbulence intensity was below 15%. The prediction of in-cylinder turbulence was performed on the cycle-resolved basis for one operating point, resulting with the information about cycle-to-cycle variations of in-cylinder turbulence during the combustion. The prediction of in-cylinder turbulence based on the measured data represents efficient inverse method whose results can be used for the faster calibration of 0D turbulence models without performing time-consuming 3-D CFD simulations.

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