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Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

This paper describes a CFD modeling based approach to address design challenges in GDI (gasoline direct injection) engine combustion system development. A Ford in-house developed CFD code MESIM (Multi-dimensional Engine Simulation) was applied to the study. Gasoline fuel is multi-component in nature and behaves very differently from the single component fuel representation under various operating conditions. A multi-component fuel model has been developed and is incorporated in MESIM code. To apply the model in engine simulations, a multi-component fuel recipe that represents the vaporization characteristics of gasoline is also developed using a numerical model that simulates the ASTM D86 fuel distillation experimental procedure. The effect of the multi-component model on the fuel air mixture preparations under different engine conditions is investigated. The modeling approach is applied to guide the GDI engine piston designs.

Recently, Ford Motor Company announced the introduction of EcoBoost engines in its Ford, Lincoln and Mercury vehicles as an affordable fuel-saving option to millions of its customers. The EcoBoost engine is planned to start production in June of 2009 in the Lincoln MKS. The EcoBoost engine integrates direct fuel injection with turbocharging to significantly improve fuel economy via engine downsizing. An application of this technology bundle into a 3.5L V6 engine delivers up to 12% better drive cycle fuel economy and 15% lower emissions with comparable torque and power as a 5.4L V8 PFI engine. Combustion system performance is key to the success of the EcoBoost engine. A systematic methodology has been employed to develop the EcoBoost engine combustion system.

The accurate prediction of fuel sprays is critical to engine combustion and emissions simulations. A fine computational mesh is often required to better resolve fuel spray dynamics and vaporization. However, computations with a fine mesh require extensive computer time. This study developed a methodology that uses a locally refined mesh in the spray region. Such adaptive mesh refinement will enable greater resolution of the liquid-gas interaction while incurring only a small increase in the total number of computational cells. The present study uses an h-refinement adaptive method. A face-based approach is used for the inter-level boundary conditions. The prolongation and restriction procedure preserves conservation of properties in performing grid refinement/coarsening. The refinement criterion is based on the mass of spray liquid and fuel vapor in each cell. The efficiency and accuracy of the present adaptive mesh refinement scheme is demonstrated.

Parallel computing schemes were developed to enhance the computational efficiency of engine spray simulations with adaptive mesh refinement (AMR). Spray simulations have been shown to be grid dependent and thus fine mesh is often used to improve solution accuracy. In this study, dynamic mesh refinement adaptive to spray region was developed and parallelized in KIVA-4. The change of cell and node numbers and the local characteristics in the dynamic mesh refinement posed difficulties in developing efficient parallel computing schemes to achieve low communication overhead and good load balance. The present strategy executed AMR on one processor with data scattering among processors following the adaptation, and performed AMR every ten computational timesteps for enhanced parallel performance. The re-initialization was required and performed at the minimized cost.

This paper proposes a film dynamics model for liquid film resulting from fuel spray impinging on a wall surface. It is based on a thin film assumption and uses numerical particles to represent the film to be compatible with the particle spray models developed previously. The Lagrangian method is adopted to govern the transport of the film particles. A new, statistical treatment was introduced of the momentum exchange between the impinging spray and the wall film to account for the directional distribution of the impinging momentum. This model together with the previously published models for outgoing droplets constitutes a complete description of the spray wall impingement dynamics. For model validation, films resulting from impinging sprays on a flat surface with different impingement angles were calculated and the results were compared with the corresponding experimental measurements.