Autoignition Correlation for Predicting Knock in Spark-Ignition Engines Fueled by Gasoline-Ethanol Blends

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. This correlation includes the effect of percentage of ethanol content, air-fuel ratio, and exhaust gas recirculation. This new correlation is developed by fitting appropriate function to the data generated by hundreds of detailed kinetics simulations. Next, the ignition delay predictions of the correlation are compared with detailed kinetics simulations for the constant volume reactor simulations. Finally, this new correlation is used to predict knock in an engine model using integral approach, and the knock onset predictions are compared with that of detailed kinetics simulations.