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An experimental study of the performance of a reverse tumble, DISI engine is reported. Specific fuel consumption and engine-out emissions have been investigated for both homogeneous and stratified modes of fuel injection. Trends in performance with varying AFR, EGR, spark and injection timings have been explored. It is shown that neural networks can be trained to describe these trends accurately for even the most complex case of stratified charge operation with exhaust gas recirculation.

The dilution of lubricating oil by fuel has adverse effects on engine wear, oil lubricity, air/fuel ratio control and feedgas emissions. Dilution is one of the factors limiting oil change intervals. The level and rate of accumulation depend on engine operating conditions and patterns of vehicle use. The work reported here develops and evaluates an empirical model to predict accumulation characteristics. This is aligned to requirements for predictions of dilution build-up in service. Predictions are shown to be in good agreement with data given in the literature. The model is used to investigate the influence of patterns of vehicle use on dilution.