Development of a Predictive Model for Knock Intensity in a Spark-Ignition Engine with Gasoline-Ethanol-nButanol Blend Fuel by Using Rapid Compression Machine 2019-24-0125

In this study, we developed a predictive model for knock intensity in spark-ignition (SI) engine with gasoline-ethanol-nbutanol (GEnB) blend fuel, which is being considered as an alternative fuel for conventional gasoline in South Korea, to understand the potential improvement of engine performance with the introduction of GEnB blend fuel. First, the ignition delay of the stoichiometric mixture of GEnB blend fuel and air was measured on a pressure of 10-30 bar and a temperature of 721-831 K by using rapid compression machine (RCM). Then, we derived the empirical correlation of the ignition delay with which the Livengood-Wu integration along pressure-temperature profile in RCM gives the best prediction for the start of combustion. The ignition delay correlation was applied to 0-D two-zone SI engine model, and we predicted the knocking intensity of GEnB blend fuels by using Livengood-Wu integration and Bougrine’s knocking intensity model. The model was validated by comparing the research octane number (RON) calculated from the model with the reference based on the cooperative fuel research (CFR) engine experiment. Consequently, it was found that the knocking prediction model properly predict RON of various GEnB blend fuels. The developed model was manipulated to predict the potential improvement of knock-limited region of modern SI engine with GEnB blend fuel, and we found that the knock-limited nIMEP increases by 1.86% as alcohol content increases by 1 % of ethanol equivalent alcohol content.