Efficient Estimation of Laminar Flame Speed in Dual-Fuel SI Engines: A Simplified Methodology for 1-D Predictive Combustion Simulation

The increasing impacts of the greenhouse effect have driven the need to reduce pollutant emissions from internal combustion engines. Renewable fuels are promising alternatives for emission reduction, and enhancing engine efficiency can further decrease specific emissions. This study explores the development of dual-fuel engines to meet these goals, focusing on dual-fuel combustion in spark-ignition (SI) engines using two different bioethanol and natural gas mixtures. A novel methodology for 1-D predictive combustion simulation in dual-fuel SI engines was developed and implemented in GT-Suite software. The approach involves a straightforward estimation of the laminar flame speed of the fuel mixture and the calibration of turbulent combustion parameters using a genetic optimization algorithm, without the need for complex chemical kinetics models. The results indicate that the proposed methodology can reproduce combustion characteristics, achieving satisfactory outcomes across most tested conditions. In the light of emerged findings, the research serves as a further baseline for future research activities dealing with dual fuel combustion in internal combustion engines.