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A quasi-dimensional computer simulation of the turbocharged spark-ignition engine has been developed in order to study system performance as various design parameters and operating conditions are varied. The simulation is of the “filling and emptying” type. Quasi-steady flow models of the compressor, intercooler, manifolds, turbine, wastegate, and ducting are coupled with a multi-cylinder engine model where each cylinder undergoes the same thermodynamic cycle. A turbulent entrainment model of the combustion process is used, thus allowing for studies of the effects of various combustion chamber shapes and turbulence parameters on cylinder pressure, temperature, NOx emissions and overall engine performance. Valve open areas are determined either based on user supplied valve lift data or using polydyne-generated cam profiles which allow for variable valve timing studies.

A naturally-aspirated, Miller cycle, Spark-Ignition (SI) engine that controls output with variable intake valve closure is compared to a conventionally-throttled engine using computer simulation. Based on First and Second Law analyses, the two load control strategies are compared in detail through one thermodynamic cycle at light load conditions and over a wide range of loads at 2000 rpm. The Miller Cycle engine can use late intake valve closure (LIVC) to control indicated output down to 35% of the maximum, but requires supplemental throttling at lighter loads. The First Law analysis shows that the Miller cycle increases indicated thermal efficiency at light loads by as much as 6.3%, primarily due to reductions in pumping and compression work while heat transfer losses are comparable.

The link between manufacturing process and product performance is studied in order to construct analytical, quantifiable criteria for the introduction of new engine technologies and processes. Cost associated with a new process must be balanced against increases in engine performance and thus demand for the particular vehicle. In this work, the effect of the Abrasive Flow Machining (AFM) technique on surface roughness is characterized through measurements of specimens, and a predictive engine simulation is used to quantify performance gains due to the new surface finish. Subsequently, economic cost-benefit analysis is used to evaluate manufacturing decisions based on their impact on firm's profitability. A demonstration study examines the use of AFM for finishing the inner surfaces of intake manifolds for two engines, one installed in a compact car and the other in an SUV.

In order to reduce hydrocarbon emission in gasoline engine, especially during warming-up period, it is necessary to estimate the fuel and fuel product flow rate in the emission gas. The intake airflow rate should also be estimated. A strategy was proposed to estimate air fuel ratio in a spark ignition engine. The mass of air in the cylinder was determined by filling-emptying method, and the fuel in the intake manifold and cylinder was estimated by the “wall-wetting” effect calculation. The use of graphical dynamic system control software is becoming more popular as automotive engineers strive to reduce the time to develop new control systems. The rapid prototype engine controller has been developed by using MATLAB, SIMULINK, REAL TIME WORKSHOP, xPC Target, and WATCOM C++. The sensor data from the engine will be transferred to computer, and the fuel delivery will be calculated.

An accurate air flow rate model is critical for high-quality air-fuel ratio control in Spark-Ignition engines using a Three-Way-Catalyst. Emerging Variable Valve Timing technology complicates cylinder air charge estimation by increasing the number of independent variables. In our previous study (SAE 2004-01-3054), an Artificial Neural Network (ANN) has been used successfully to represent the air flow rate as a function of four independent variables: intake camshaft position, exhaust camshaft position, engine speed and intake manifold pressure. However, in more general terms the air flow rate also depends on ambient temperature and pressure, the latter being largely a function of altitude. With arbitrary cam phasing combinations, the ambient pressure effects in particular can be very complex. In this study, we propose using a separate neural network to compensate the effects of altitude on the air flow rate.

Adaptive valve timing control is one of the promising techniques to accomplish the optimized mixture formation and combustion depending on the load and speed, which is needed to meet the future challenges of reducing fuel consumption and exhaust emissions. The behavior and the effect of adaptive valve timing control system has been investigated by computer simulation, which simulates the gas dynamics in engines. These programs are typically one-dimensional including complex flow features as ‘special’ boundaries. A code adopting 2-step Lax-Wendroff method with artificial damping terms called FCT(Flux Corrected Transport), was developed to investigate the influence of operational and design parameters on the performance of engines. The effects of adaptive valve timing control system on volumetric efficiency or engine torque, and pumping loss were investigated. It increased low end torque by about 6%, and reduced pumping loss drastically at low load, high engine speed conditions.