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A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

The performance of a commercial Cu-zeolite SCR catalyst after differing degrees of hydrothermal aging (aged for 72 hours at 500, 700 and 800°C with 10% moisture balanced with air) was studied by spatially resolving different key reactions using gas-phase FTIR measurements. Gases were sampled along a channel at different positions and analyzed using FTIR, which overcomes the interference of water and nitrogen on ammonia concentration detection encountered in standard mass spectrometer-based spatial resolution measurements. The NO:NO₂ concentration ratio was changed so that the standard (NO:NO₂ = 1:0), fast (NO:NO₂ = 1:1) and NO₂ (NO:NO₂ = 0:1) SCR reactions could be investigated as a function of the catalyst's hydrothermal aging extent. In addition, the effects of hydrothermal aging on the activity of NH₃ and NO oxidation were also investigated. Hydrothermal aging had little effect on NO oxidation activity.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

Unique silver/alumina (Ag-Al₂O₃) catalysts developed using high-throughput discovery techniques in collaboration with BASF Corporation were investigated at General Motors Corporation under simulated lean-burn engine exhaust feed conditions for the selective catalytic reduction of NOx using hydrocarbons (HC-SCR). Hydrocarbon mixtures were used as the reductant to model the multi-component nature of diesel fuel and gasoline. Previous work has shown promising HC-SCR results in both laboratory reactor and engine dynamometer testing. This report investigates several aspects of HC-SCR catalyst durability, including thermal durability, sulfur tolerance, and hydrocarbon deactivation.

A unique catalyst developed using high-throughput discovery techniques in collaboration with BASF Corporation and Accelrys, Inc. was investigated at General Motors under simulated diesel engine exhaust feed conditions for the selective catalytic reduction of NOx. A hydrocarbon mixture was used as the reductant to model the multi-component nature of diesel fuel and the catalyst was evaluated over a wide range of temperatures (150 - 550°C) relevant to light-duty diesel exhaust. This report investigates the effects of NOx (as NO or NO2), hydrocarbon concentration level (HC:NOx ratio), oxygen concentration, NO concentration, catalyst space velocity, catalyst temperature, and the co-presence of hydrogen on steady-state NOx reduction activity. Using these results, a control strategy was developed to maximize NOx conversion over the wide-ranging exhaust conditions likely to be encountered in light-duty diesel applications.

A modified version of the multi-dimensional KIVA-II code is used to model the effects of multiple injection schemes and exhaust gas recirculation (EGR) on direct injected diesel engine NOx and soot emissions. The computational results, which also considered double and triple injection schemes and varying EGR amounts, are compared with experimental data obtained from a single cylinder version of a Caterpillar heavy-duty truck engine. The study is done at high load (75% of peak torque at 1600 rpm) where EGR is known to produce unacceptable increases in soot (particulate). The effect of soot and spray model formulations are considered. This includes a new spray model based on Rayleigh-Taylor instabilities for liquid breakup. A soot oxidation model that accounts for turbulent mixing and kinetic effects were found to give accurate results. The results showed excellent agreement between predicted and measured in-cylinder pressure, and heat release data for the various cases.

The University of Wisconsin-Madison Snowmobile Team designed and constructed a hybrid-electric snowmobile for the 2005 Society of Automotive Engineers' Clean Snowmobile Challenge. Built on a 2003 cross-country touring chassis, this machine features a 784 cc fuel-injected four-stroke engine in parallel with a 48 V electric golf cart motor. The 12 kg electric motor increases powertrain torque up to 25% during acceleration and recharges the snowmobile's battery pack during steady-state operation. Air pollution from the gasoline engine is reduced to levels far below current best available technology in the snowmobile industry. The four-stroke engine's closed-loop EFI system maintains stoichiometric combustion while dual three-way catalysts reduce NOx, HC and CO emissions by up to 94% from stock. In addition to the use of three way catalysts, the fuel injection strategy has been modified to further reduce engine emissions from the levels measured in the CSC 2004 competition.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

The lift-off length plays a significant role in spray combustion as it influences the air entrainment upstream of the lift-off location and hence the soot formation. Accurate prediction of lift-off length thus becomes a prerequisite for accurate soot prediction in lifted flames. In the present study, KIVA-3v coupled with CHEMKIN, as developed at the Engine Research Center (ERC), is used as the CFD model. Experimental data from the Sandia National Labs. is used for validating the model predictions of n-heptane lift-off lengths and soot formation details in a constant volume combustion chamber. It is seen that the model predictions, in terms of lift-off length and soot mass, agree well with the experimental results for low ambient density (14.8 kg/m3) cases with different EGR rates (21% O2 - 8% O2). However, for high density cases (30 kg/m3) with different EGR rates (15% O2 - 8% O2) disagreements were found.

Fundamental simulations in a quiescent cell under adiabatic conditions were made to understand the effect of temperature, equivalence ratio and the components of the recirculated exhaust gas, viz., CO2 and H2O, on the combustion of n-Heptane. Simulations were made in single phase in which evaporated n-Heptane was uniformly distributed in the domain. Computations were made for two different temperatures and four different EGR levels. CO2 or H2O or N2was used as EGR. It was found that the initiation of the main combustion process was primarily determined by two competing factors, i.e., the amount of initial OH concentration in the domain and the specific heat of the mixture. Further, initial OH concentration can be controlled by the manipulating the ambient temperature in the domain, and the specific heat capacity of the mixture via the mixture composition. In addition to these, the pre combustion and the subsequent post combustion can also be controlled via the equivalence ratio.

A study of partially premixed combustion (PPC) with non-oxygenated 91 pump octane number1 (PON) commercially available gasoline was performed using a heavy-duty (HD) compression-ignition (CI) 2.44 l Caterpillar 3401E single-cylinder oil test engine (SCOTE). The experimental conditions selected were a net indicated mean effective pressure (IMEP) of 11.5 bar, an engine speed of 1300 rev/min, an intake temperature of 40°C with intake and exhaust pressures of 200 and 207 kPa, respectively. The baseline case for all studies presented had 0% exhaust gas recirculation (EGR), used a dual injection strategy a -137 deg ATDC pilot SOI and a -6 deg ATDC main start-of-injection (SOI) timing with a 30/70% pilot/main fuel split for a total of 5.3 kg/h fueling (equating to approximately 50% load). Combustion and emissions characteristics were explored relative to the baseline case by sweeping main and pilot SOI timings, injection split fuel percentage, intake pressure, load and EGR levels.

The two most common NOx reducing technologies, in an oxygen abundant exhaust stream, are urea selective catalytic reduction urea-SCR and lean NOx trap (LNT) catalysts. Each technology has advantages and disadvantages. Another selective catalytic reduction (SCR) catalyst that uses hydrocarbons (HC-SCR), specifically diesel fuel, as the reductant to reduce NOx emissions was investigated. This catalyst is a result of a high throughput discovery project and conducted in cooperation with BASF, Accelrys and funded by the Department of Energy (DOE.) Several full size 5.0L monolith catalysts were made and evaluated using a V6 turbo charged diesel engine connected to a dynamometer running light-duty transient test cycles. The NOx efficiency on the HWYFET and US06 tests were measured to be 92% and 76% respectively. The FTP was 60% on a weighted basis.

At the current state of diesel engine technology, all diesel engines require some sort of NOx control device to comply with Tier II Bin 5 light-duty or 2010 heavy-duty NOx emission standards. Selective Catalytic Reduction of NOx with hydrocarbons (HC-SCR) to reduce NOx from diesel exhaust emissions is an attractive technology for lean NOx control, especially when diesel fuel is used as the reductant. However, it has been reported that when diesel fuel is used as the reductant catalyst deactivation occurred. Even though this kind of deactivation is reversible at high enough temperatures, it is a deficiency that needs to be overcome for the successful implementation of the technology. We studied the HC-SCR catalyst deactivation using diesel fuel as the reductant. The variables investigated included catalyst temperature, HC:NOx ratio, NOx concentration, and space velocity. The results showed that one single parameter can be used to measure the catalyst deactivation: the HC-SCR activity.

To comply with Tier II Bin 5 light-duty or 2010 heavy-duty NOx emission standards, all diesel engines require some sort of NOx control device. Selective Catalytic Reduction of NOx with hydrocarbons (HC-SCR) to reduce NOx from diesel exhaust emissions is an attractive technology for lean NOx control, especially when diesel fuel is used as the reductant. However, it has been reported that when diesel fuel is used as the reductant catalyst deactivation occurred (1). In a companion paper, we demonstrated that the HC-deactivation is caused by the mismatch of the adsorption and desorption processes of either the reactants or the products of a normal SCR reaction (2). In this paper, we probe the nature of the catalyst deactivation with various reductants. Both hydrocarbons and oxygenates were used as the reductants. The deactivation or the mismatch in adsorption and desorption rates is molecular size or chain length dependent.

A unique silver/alumina selective catalytic reduction (SCR) catalyst which used hydrocarbons (HC-SCR) to reduce NOx emissions was investigated. Diesel fuel or ethanol were used as the reductants to evaluate catalyst performance. Several full size 5.0L monolith 2.0 and 3.0 wt.% Ag2O-Al2O3 catalysts were created. Testing was conducted using a 6.6L Duramax turbocharged heavy duty diesel engine. Dynamometer testing on the heavy duty FTP and SET 13 transient test cycles was conducted. The NOx conversion efficiency was evaluated as a function of catalyst volume, inlet cone angle, hydrocarbon to NOx ratio (HC:NOx), and space velocity. Oxygen effects on the NOx reaction and the HC slip past the HC-SCR catalyst were also determined. An FTIR was used to evaluate unregulated emissions. Testing on the heavy duty FTP and SET 13 test cycles, with diesel fuel as the reductant, resulted in a 60% and 65% NOx conversion reduction respectively.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

A study of the combined use of split injections, EGR, and flexible boosting was conducted. Statistical optimization of the engine operating parameters was accomplished using a new response surface method. The objective of the study was to demonstrate the emissions and fuel consumption capabilities of a state-of-the-art heavy -duty diesel engine when using split injections, EGR, and flexible boosting over a wide range of engine operating conditions. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. Similarly, boost has been shown to be an important parameter to optimize. During the experiments, an instrumented single-cylinder heavy -duty diesel engine was used.

The steady-state reduction of NOx at temperatures between 150-300°C has been investigated under simulated lean-burn conditions using a two-stage transient flow reactor system consisting of non-thermal plasma in combination with a sodium Y zeolite catalyst. Reactivity comparisons were made with and without plasma operation in order to identify the plasma-generated hydrocarbon species necessary for the selective catalytic reduction (SCR) of NOx. With propene as the hydrocarbon in the feed, NO is completely oxidized to NO2 in the plasma and the formation of oxidized carbon-containing species include formaldehyde, acetaldehyde, carbon monoxide, carbon dioxide, and methanol. Fourier transform infrared (FTIR) measurements indicate a close carbon balance between plasma inlet and outlet gas feed concentrations, signifying the major species have been identified.

Past research has shown that reactivity controlled compression ignition (RCCI) combustion offers efficiency and NOx and soot advantages over conventional diesel combustion at mid load conditions. However, at high load and low speed conditions, the chemistry timescale of the fuel shortens and the engine timescale lengthens. This mismatch in timescales makes operation at high load and low speed conditions difficult. High levels of exhaust gas recirculation (EGR) can be used to extend the chemistry timescales; however, this comes at the penalty of increased pumping losses. In the present study, targeting the high load - low speed regime, computational optimizations of RCCI combustion were performed at 20 bar gross indicated mean effective pressure (IMEP) and 1300 rev/min. The two fuels used for the study were gasoline (low reactivity) and diesel (high reactivity).