Session: 06-01 SI Engine Modeling

Track: Track 6: Modeling and Simulation

Paper Number: 90780

90780 - Impact of Low- and High-Temperature Chemistry on Engine Knock Prediction 

The cost of 3D simulations of SI engine combustion and knock prediction is strongly influenced by the size of the chemical kinetic model used. Incorporating low-temperature chemistry for a multicomponent fuel substantially increases the size of the resulting chemical kinetic model, hence higher computational cost. It is generally assumed that low-temperature chemistry modeling is indispensable for the accurate prediction of knock. It is even sometimes further assumed that a high-temperature chemical kinetic model is incapable of predicting any useful features of engine knock. But it is of interest to quantify the differences between knock prediction using a detailed chemical kinetic model with low-temperature kinetics and knock prediction using a reduced version of the detailed model for high-temperature kinetics.

In this paper, a reduced high-temperature chemical model is first obtained using Alternate Species Elimination from the detailed chemical model that includes low-temperature chemistry of a multicomponent gasoline surrogate. The prediction of engine knock using low-temperature detailed chemical model is then contrasted with the prediction using the reduced version. The 3D CFD engine simulations are based on a Direct-Injection single-cylinder SI engine with a compression ratio of 14 and a flat-head piston. To predict the onset of knock, the flame propagation is captured using the G-equation model while the evolution toward local auto-ignition is determined through finite rate chemical kinetic simulations within the computational cell.

Both the reduction and the comparison of knock predictions offer some insight into the underlying chemistry and time scales that control knock phenomena. The results are useful for cost-effective engine knock prediction.

Keywords: engine knock, Low-temperature chemistry, High-temperature chemistry, mechanism reduction

Presenting Author: Ahmet Serhat Bahar Syracuse University