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Boosted Homogeneous Charge Compression Ignition (HCCI) has been modeled and has demonstrated the potential to extend the engine's upper load limit. A commercially available engine simulation software (GT-PowerÖ) coupled to the University of Michigan HCCI combustion and heat transfer correlations was used to model a 4-cylinder boosted HCCI engine with three different boosting configurations: turbocharging, supercharging and series turbocharging. The scope of this study is to identify the best boosting approach in order to extend the HCCI engine's operating range. The results of this study are consistent with the literature: Boosting helps increase the HCCI upper load limit, but matching of turbochargers is a problem. In addition, the low exhaust gas enthalpy resulting from HCCI combustion leads to high pressures in the exhaust manifold increasing pumping work. The series turbocharging strategy appears to provide the largest load range extension.

The growing presence of Spark Ignition Direct Injection (SIDI) engines along with the prevalence of direct injected Compression Ignition (CI) engines results in the requirement of Particulate Matter (PM) exhaust abatement. This occurs through the implementation of Gasoline Particulate Filters (GPFs) and Diesel Particulate Filters (DPFs). Modeling of GPFs and DPFs are analogous because of the similar flow patterns and wall flow PM capture methodology. Conventional modeling techniques include a two-channel (inlet/outlet) formulation that is applicable up to three-dimensions. However, the numerical stiffness that results from the need to couple the solution of these channels in compressible flow can result in relatively long run times. Previously, the author presented a lumped DPF model using dynamically incompressible flow intended for an Engine Control Unit (ECU) in order to generate a model that runs faster than real time using a high-level programming language.

Particulate filters (PF) are a highly effective after-treatment device that reduces particulate matter emissions, a rising environmental concern in the automotive industry. However, accumulation of solid particles during the PF filtration process increases engine backpressure considerably, which can have a negative impact on engine efficiency, acoustics, and gaseous emissions. In this area, an accurate pressure drop model helps to better understand the effect of accumulated solid particles in the PF on engine backpressure, aiding in design and regeneration considerations without physical testing. These effects are further improved on board the vehicle using a single equation pressure drop model with a relatively low computational cost. This article presents a thorough history of PF pressure drop models and their advancements.

A comprehensive methodology for predicting the transient thermal response of spark-ignition engines subject to time-varying boundary conditions is presented. The approach is based on coupling a cycle-resolved quasi-dimensional simulation of in-cylinder thermodynamic events with a resistor-capacitor (R-C) thermal network of the various component and fluid interactions throughout the engine and exhaust system. The dynamic time step of the thermal solution is limited by either the frequency of the prescribed time-dependent boundary conditions or by the minimum thermal time constant of the R-C network. To demonstrate the need for fully-coupled, transient thermodynamic and heat transfer solutions, model behavior is first explored for step-change and staircase variations of engine operating conditions.

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.

In this paper, the available correlations proposed in the literature for the gas-side heat transfer in the intake and exhaust system of a spark-ignition internal combustion engine were surveyed. It was noticed that these only by empirically fitted constants. This similarity provided the impetus for the authors to explore if a universal correlation could be developed. Based on a scaling approach using microscales of turbulence, the authors have fixed the exponential factor on the Reynolds number and thus reduced the number of adjustable coefficients to just one; the latter can be determined from a least squares curve-fit of available experimental data. Using intake and exhaust side data, it was shown that the universal correlation The correlation coefficient of this proposed heat transfer model with all available experimental data is 0.845 for the intake side and 0.800 for the exhaust side.

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.

Software packages including Argonne National Lab's Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model and the EPA's Motor Vehicle Emissions Simulation (MOVES) model are useful in analyzing the emission profiles of light-duty vehicles. In particular, GREET performs a detailed life cycle fuel energy and emissions analysis, while MOVES focuses on energy and emissions during vehicle operation. This study uses MOVES2010b in the creation of emission trends in order to predict future emissions regulations and the subsequent aftertreatment device areas of improvement required to meet these standards. A second objective was to create four time sheet tables in order to update the base vehicle operation emission profiles used in GREET. The simulation results depict the balance between nitrous oxide and hydrocarbon emissions, the dependency upon climate effects, and areas for potential improvement given recent engine design trends.

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.

Five small two-stroke engine designs were tested at different air/fuel ratios, under steady state and transient cycles. The effects of combustion chamber design, carburetor design, lean burning, and fuel composition on performance, hydrocarbon and carbon monoxide emissions were studied. All tested engines had been designed to run richer than stoichiometric in order to obtain satisfactory cooling and higher power. While hydrocarbon and carbon monoxide emissions could be greatly reduced with lean burning, engine durability would be worsened. However, it was shown that the use of a catalytic converter with acceptably lean combustion was an effective method of reducing emissions. Replacing carburetion with in-cylinder fuel injection in one of the engines resulted in a significant reduction of hydrocarbon and carbon monoxide emissions.

An early-design methodology for predicting both expected fuel economy and catalyst-out CO, HC and NOx concentrations during arbitrarily-defined transient cycles is presented. The methodology is based on utilizing a vehicle-powertrain model with embedded maps of fully warmed up engine-out performance and emissions, and appropriate temperature-dependent correction factors to account for not fully warmed up conditions during transients. Similarly, engine-out emissions are converted to catalyst-out emissions using conversion efficiencies based on the catalyst brick temperature. A crucial element of the methodology is hence the ability to predict heat flows and component temperatures in the engine and the exhaust system during transients, consistent with the data available during concept definition and early design phases.

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.

Diesel Particulate Filters (DPFs) have become a required aftertreatment device for Compression Ignition engine exhaust cleanup of Particulate Matter (PM). Moreover, with the increased prevalence of Spark Ignition Direct Injection (SIDI) systems, discussions are currently underway regarding the need of Gasoline Particulate Filters to handle the PM emanating from their combustion process. In this area, the two-channel DPF model has been widely successful in predicting the temperature, pressure drop, and species conversion in these devices. Because of the need to simulate compressible flow through the channels and a porous wall, these models have a difficult time achieving real-time predictive results suitable for an Engine Control Unit (ECU). As a result, this effort describes the creation of a lumped DPF model intended for an ECU. Model formulation was based on the standard governing equations, but simplified in order to remove as much computational overhead as possible.

Significant progress towards reducing diesel engine fuel consumption and emissions is possible through the simultaneous Waste Heat Recovery (WHR) and Particulate Matter (PM) filtration in a novel device described here as a Diesel Particulate Filter Heat Exchanger (DPFHX). This original device concept is based on the shell-and-tube heat exchanger geometry, where enlarged tubes contain DPF cores, allowing waste heat recovery from engine exhaust and allowing further energy capture from the exothermic PM regeneration event. The heat transferred to the working fluid on the shell side of the DPFHX becomes available for use in a secondary power cycle, which is an increasingly attractive method of boosting powertrain efficiency due to fuel savings of around 10 to 15%. Moreover, these fuel savings are proportional to the associated emissions reduction after a short warm-up period, with startup emissions relatively unchanged when implementing a WHR system.