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Adjusting the Residual Gas Fraction (RGF) by means of Variable Valve Actuation (VVA) is a strong candidate for controlling the ignition timing in Homogeneous Charge Compression Ignition (HCCI) engines. However, at high levels of residual gas fraction, insufficient mixing can lead to the presence of considerable temperature and composition variations. This paper extends previous modeling efforts to include the effect of RGF distribution on the onset of ignition and the rate of combustion using a multi-dimensional fluid mechanics code (KIVA-3V) sequentially with a multi-zone code with detailed chemical kinetics. KIVA-3V is used to simulate the gas exchange processes, while the multi-zone code computes the combustion event. It is shown that under certain conditions the effect of composition stratification is significant and cannot be captured by a single-zone model or a multi-zone model using only temperature zones.

The present study introduces a modeling approach for investigating the effects of valve events and gas exchange processes in the framework of a full-cycle HCCI engine simulation. A multi-dimensional fluid mechanics code, KIVA-3V, is used to simulate exhaust, intake and compression up to a transition point, before which chemical reactions become important. The results are then used to initialize the zones of a multi-zone, thermo-kinetic code, which computes the combustion event and part of the expansion. After the description and the validation of the model against experimental data, the application of the method is illustrated in the context of variable valve actuation. It has been shown that early exhaust valve closing, accompanied by late intake valve opening, has the potential to provide effective control of HCCI combustion.

Selective Catalytic Reduction (SCR) catalysts used in Lean NOx Trap (LNT) - SCR exhaust aftertreatment systems typically encounter alternating oxidizing and reducing environments. Reducing conditions occur when diesel fuel is injected upstream of a reformer catalyst, generating high concentrations of hydrogen (H₂), carbon monoxide (CO), and hydrocarbons to deNOx the LNT. In this study, the functionality of an iron (Fe) zeolite SCR catalyst is explored with a bench top reactor during steady-state and cyclic transient SCR operation. Experiments to characterize the effect of an LNT deNOx event on SCR operation show that adding H₂ or CO only slightly changes SCR behavior with the primary contribution being an enhancement of nitrogen dioxide (NO₂) decomposition into nitric oxide (NO). Exposure of the catalyst to C₃H₆ (a surrogate for an actual exhaust HC mixture) leads to a significant decrease in NOx reduction capabilities of the catalyst.

A global, systems-level model which characterizes the thermal behavior of internal combustion engines is described in this paper. Based on resistor-capacitor thermal networks, either steady-state or transient thermal simulations can be performed. A two-zone, quasi-dimensional spark-ignition engine simulation is used to determine in-cylinder gas temperature and convection coefficients. Engine heat fluxes and component temperatures can subsequently be predicted from specification of general engine dimensions, materials, and operating conditions. Emphasis has been placed on minimizing the number of model inputs and keeping them as simple as possible to make the model practical and useful as an early design tool. The success of the global model depends on properly scaling the general engine inputs to accurately model engine heat flow paths across families of engine designs. The development and validation of suitable, scalable submodels is described in detail in this paper.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

Despite remarkable progress made over the past 30 years, automobiles continue to be a major source of hydrocarbon emissions. The objective of this study is to evaluate whether variable exhaust valve opening (EVO) and exhaust valve closing (EVC) can be used to reduce hydrocarbon emissions. An automotive gasoline engine was tested with different EVO and EVC timings under steady-state and start-up conditions. The first strategy that was evaluated uses early EVO with standard EVC. Although exhaust gas temperature is increased and catalyst light-off time is reduced, the rapid drop in cylinder temperature increases cylinder-out hydrocarbons to such a degree that a net increase in hydrocarbon emissions results. The second strategy that was evaluated uses early EVO with early EVC. Early EVO reduces catalyst light-off time by increasing exhaust gas temperature and early EVC keeps the hydrocarbon-rich exhaust gas from the piston crevice from leaving the cylinder.