Flame Propagation Speed in SI Engines: Modeling and Experimental Assessment

Abstract

The necessity for further reductions of in-cylinder pollutant formation and the opportunity to minimize engine development and testing time highlight the need of cycle simulation tools that have to accurately predict the effects of fuel, design and operating variables on engine performance. To develop reliable tools for indicated cycle simulation in SI engines, a correct prediction of heat release is required, which, in turn, involves the evaluation of in-cylinder turbulence generation and flame-turbulence interaction. This can be pursued by the application of a combustion fractal model coupled with semiempirical correlations of available geometrical and thermodynamical mass-averaged quantities. However, in the literature there is a lack of comparisons between the flame propagation speed obtained through these correlations and the experimental data determined under operating conditions that are significant for IC engines running on both conventional and alternative fuels. The present paper develops a new correlation that takes account of the effects of turbulence shrinking on the flame front as well as of the turbulent transfer of both species and heat across the flame front. The procedure has been applied to calculate the burning speeds in the cylinder of a naturally-aspirated bi-fuel engine for a wide range of engine speeds (N = 2000–4600 rpm), loads (bmep = 200–790 kPa), relative air-fuel ratios (RAFR = 0.80–1.30) and spark-advances (SA ranging from 8 deg retard to 2 deg advance with respect to MBT), under both gasoline and CNG operations. The computed burning speeds were compared to those obtained with the correlations currently available in the literature and to the experimental flame propagation data. These latter were extracted from measured in-cylinder pressure by means of a diagnostics technique previously developed by the authors. The results indicate that the burning speeds calculated through the authors’ procedure are in better agreement with the experimental outcomes than those derived from the correlations that are currently available in the literature.