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In recent times new tools have emerged to aid the optimization of engine design. The particle swarm optimizer, used here is one of these tools. However, applying it to the optimization of the S.I. engine for high efficiency and low NOx emission has shown the preference of ultra lean burn strategy combined with high compression ratios. For combined power, efficiency and emissions benefits, there are two restricting factors, limiting the applicability of this strategy, knocking and cyclic variability. In the ultra lean region, knocking is not an important issue but the variability is a major concern. This paper demonstrates the application of a variability model to limit the search domain for the optimization program. The results show that variability constrains the possible gains in fuel consumption and emission reduction, through optimizing cam phasing, mixture and spark timing. The fuel consumption gain is reduced by about 11% relative.

In spark ignited engine maximum thermal efficiency is found with lean mixtures. The authors' models for optimizing engine design show a preference for burning at the lean limit which to date has been found from experimental measurements. Hence ignoring combustion variability in the modeling can cause significant error in engine performance and emissions at or close to the lean limit. To aid in optimizing engine design, a model is needed that allows the inclusion of variability in the search for lean operation solutions. Here a useful addition to modeling is presented - a physically based lean limit model that can allow the lean limit to be set as non-dimensional COV of IMEP or as a variance in IMEP. The current work focuses on predicting the increase of cyclic variability due to the dilution of the mixture, whether by EGR and residual gas or by excess air.

In this paper the experimental performance of the lean limits is examined for two different types of engines the first a dedicated LPG high compression ratio 2-valve per cylinder engine (Ford of Australia MY 2001 AU Falcon) and the second a gasoline moderate compression 4-valve per cylinder variant of the same engine (Ford of Australia MY 2006 BF Falcon). The in-cylinder composition at the lean limit over a range of steady state operating conditions is estimated using a quasi-dimensional model. This makes it possible to take into account the effects of both residual fraction and fresh charge diluents (EGR and excess air) that allow the exploration of a modeled lean limit performance [1, 2]. The results are compared to the predictions from a model for combustion variability applied to the quasi-dimensional model operating in optimization mode.

The challenge of tough fuel consumption reduction targets and near zero NOx emission standards can be met by optimization of the full range of engine design variables. Here these are explored through an engine simulation model and the application of an optimizing algorithm that can work in discontinuous data space. The combustion model has main features that include flame propagation, the effects of turbulence, chamber shape interaction and NOx formation. Two engine configurations are used to illustrate the application of the model and optimizer. Both allow the adoption of extra lean burn possible with LPG as fuel and EGR through an external route or cam phasing. In the first the compression ratio and cam profiles are fixed, in the second study they are also optimized.