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The turbulent flow field inside the cylinder plays a major role in spark ignition (SI) engines. Multiple phenomena that occur during the high pressure part of the engine cycle, such as early flame kernel development, flame propagation and gas-to-wall heat transfer, are influenced by in-cylinder turbulence. Turbulence inside the cylinder is primarily generated via high shear flows that occur during the intake process, via high velocity injection sprays and by the destruction of macro-scale motions produced by tumbling and/or swirling structures close to top dead center (TDC) . Understanding such complex flow phenomena typically requires detailed 3D-CFD simulations. Such calculations are computationally very expensive and are typically carried out for a limited number of operating conditions. On the other hand, quasi-dimensional simulations, which provide a limited description of the in-cylinder processes, are computationally inexpensive.

Autoignition correlations are widely used to predict knock in internal combustion engines as opposed to detailed kinetics mechanisms involving hundreds of reactions due to computational cost. Several autoignition correlations exist in the literature for different fuels, and their functional form depends on the operating parameters like fuel type and temperature range, among other things. In the literature different types of correlations are proposed for gasoline fuel, but to the best of the authors’ knowledge none of these correlations can be used for gasoline-ethanol blends with varying levels of ethanol percentage and a wide range of equivalence ratios and temperatures. In this paper, a new empirical correlation is developed to predict the autoignition of gasoline-ethanol blends over a wide range of temperatures including Negative Temperature Coefficient (NTC) region.