Full Cycle Engine Simulations with Detailed Chemistry

Abstract: The modeling work developed in this thesis can be divided in two main areas of investigations: autoignition related to spark ignition engine and combustion and emissions formation in relation to diesel engines. A first version of a detailed kinetics engine simulation program, extended to handle full cycle calculations, was employed in order to demonstrate the strong effect that nitric oxide from the residual gas has on the autoignition onset. It was found that a concentration of about 500 ppm in the intake gas determines a maximal promotion of autoignition. Increased simulation capabilities were achieved by integrating the in house detailed kinetic code into a commercial 1-D engine program. By this it was possible on one hand to have a simulation tool able to handle detailed kinetics and thus have control over combustion and emissions, and on the other hand to monitor global engine operation conditions. Further accuracy on autoignition was achieved by employing a stochastic reactor model (SRM) for spark ignition engine calculations. Based on the probability density function (PDF) this approach was able to model phenomena with strong influence on engine knock as: turbulent mixing and inhomogeneities, phenomena usually neglected by regular existing engine programs. While keeping computational time low and still using detailed chemistry, good correlative results were obtained with the stochastic approach. For the second part of the work, the stochastic reactor model was applied for diesel engine combustion and emissions investigations. The purpose of this implementation was primarily the calculation of NOx emissions and soot within diesel engines. Soot calculations were based on the method of moments. Comparisons of soot production with measured data from a carbon black reactor indicate good agreement. The diesel SRM model was applied on a FIAT car engine and on a low speed marine engine. The model is capable to correlate the ignition timing and to indicate the trends in NOx and soot generation.