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In today's search for a better fuel economy and lower emissions, it is essential to precisely control the injected fuel quantity, as demanded by the engine load, into each of the engine cylinders. In fuel injection systems, the pressure pulsations due to the rapid opening and closing of the injectors can cause uneven injected fuel amounts between cylinders. In order to develop effective techniques to reduce these pressure pulsations, it is crucial to have a good understanding of the dynamic characteristics of such fuel injection systems. This paper presents the benefits of using simulation as a tool to analyze the dynamic behaviors of a V8 gasoline injection system. The fuel system modeling, based on a one-dimensional (1D) lumped parameter approach, has been developed in the AMESim® environment. The comparison between the simulation results and the experimental data shows good agreement in fluid transient characteristics for both time and frequency domains.

The fluid flow in a direct-injection gasoline diaphragm fuel pump is analyzed using a multi-physics simulation program. The analysis accounts for fully coupled fluid-structure interactions (FSI), the effects of the diaphragm movement and its deformation, the FSI between the diaphragm and the fluid, the FSI between the inlet/outlet valves and the fluid, and the solid-solid contact between the inlet/outlet valves and the valve seats. The flow rate of the fuel pump under various cam speeds is examined. The accuracy of the predictions for the flow rate of the fuel pump is assessed through comparisons with the experimental data, and moderately good agreement is obtained. In addition, some conclusions based on this study are summarized for reference.

Optimization of the mechanical aspects of a heated conical oxygen sensor for desired performances, such as low heater power, good poison resistance, fast light-off, and broad temperature range, etc. was achieved with computer modeling. CFD analysis was used to model the flow field in and around a sensor in an exhaust pipe to predict the convection coefficients, poisoning, and switching time. Heat transfer analysis coupled with electrical heating was applied to predict temperature and light-off time. Results of the optimization are illustrated, with good agreements between modeling and testing.