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A review of flame kernel growth in SI engines and the regimes of premixed turbulent combustion showed that a misfire model based on regimes of premixed turbulent combustion was warranted[1]. The present study will further validate the misfire model and show that it has captured the dominating physics and avoided extremely complex, yet inefficient, models. Results showed that regimes of turbulent combustion could, indeed, be used for a concept-simple model to predict misfire limits in SI engines. Just as importantly, the entire regimes of premixed turbulent combustion in SI engines were also mapped out with the model.

Lean mixture combustion might be an important feature in the next generation of SI engines, while diluents (internal and external EGR) have already played a key role in the reductions of emissions and fuel consumption. Lean burn modeling is even more important for engine modeling tools which are sometimes used for new engine development. The effect of flame strain on flame speed is believed to be significant, especially under lean mixture conditions. Current quasi-dimensional engine models usually do not include flame strain effects and tend to predict burn rate which is too high under lean burn conditions. An attempt was made to model flame strain effects in quasi-dimensional SI engine models. The Ford model GESIM (stands for General Engine SIMulation) was used as the platform. A new strain rate model was developed with the Lewis number effect included.

In premixed turbulent combustion models, two mechanisms have been used to explain the increase in the flame speed due to the turbulence. The newer explanation considers the full range of turbulence scales which wrinkle the flame front so as to increase the flame front area and, thus, the flame propagation speed. The fractal combustion model is an example of this concept. The older mechanism assumes that turbulence enables the penetration of unburned mixtures across the flame front via entrainment into the burned mixture zone. The entrainment combustion or eddy burning model is an example of this mechanism. The results of experimental studies of combustion regimes and the flame structures in SI engines has confirmed that most combustion takes place at the wrinkled flame front with additional combustion taking place in the form of flame fingers or peninsulas.

Tumble flow has been recognized as an important and positive enhancement of combustion for SI engines. Tumble flow modeling with quasi-dimensional models is difficult because of the transient nature of tumble vortex, compared with swirl flows. Although multi-dimensional models have obtained plenty of attention recently in engine research, quasi-dimensional SI engine models will continue to dominate industrial applications in the near future. In the present research, a bulk flow model has been developed for tumble flows based on angular momentum conservation. Its effect on turbulence was then modeled using a Two-Equation Model (k-ε Model). A methodology has also been developed to use particle tracking velocimetry (PTV) measurement to calibrate the quasi-dimensional bulk flow model at engine BDC to model tumble vortex and tumble-generated turbulence. The Entrainment Combustion Model was used for combustion modeling.

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.