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Detailed knowledge of hydrocarbon fuel combustion chemistry has grown tremendously in recent years. However, the gap between detailed chemistry and computational fluid dynamics (CFD) remains, because of the high cost of solving detailed chemistry in a large number of computational cells. This paper presents the results of applying a suite of techniques aimed at closing this gap. The techniques include use of a surrogate blend optimizer and a guided mechanism reduction methodology, as well as advanced methods for efficiently and accurately coupling the pre-reduced kinetic models with the multidimensional transport equations. The advanced methods include dynamic adaptive chemistry (DAC) and dynamic cell clustering (DCC) algorithms.

System level modeling was used to develop a suitable control strategy for Diesel Homogeneous Charge Compression Ignition (HCCI) transient operation. Intake temperature and pressure, engine speed, engine load, cylinder wall temperature, exhaust gas recirculation, etc. all significantly affect combustion phasing generating a scenario where simple ECU mapping techniques prove inadequate. Two-stage fuels such as diesel fuel pose additional challenges for accurate combustion control. Low-temperature cool-flame chemical heat release can significantly alter the thermodynamic state of the trapped gaseous mixture and hence combustion phasing. Operator and environmentally induced transients can rapidly alter combustion phasing parameters suggesting a need for model-based control. A model-based control strategy featuring the identified essential physics has been developed to control diesel HCCI combustion phasing through transient operation.