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Methane abatement in the exhaust gas of natural gas engines is much more challenging in respect to the oxidation of other higher order hydrocarbons. Under steady state λ sweep, the methane conversion efficiency is high at exact stoichiometric, and decreases steeply under both slightly rich and slightly lean conditions. Transient lean to rich transitions can improve methane conversion at the rich side. Previous experimental work has attributed the enhanced methane conversion to activation of methane steam reforming. The steam reforming rate, however, attenuates over time and the methane conversion rate gradually converges to the low steady state values. In this work, a reactor model is established to predict steady state and transient transition characteristics of a three-way catalyst (TWC) mounted in the exhaust of a natural gas heavy-duty engine.

The selective catalytic reduction has seen widespread adoption as the best technology to reduce the NOx emissions from internal combustion engines, particularly for Diesels. This technology uses ammonia as a reducing agent, which is obtained injecting an ammonia carrier into the exhaust gas stream. The dosing of the ammonia carrier, usually AdBlue, is the major concern during the design and engine calibration phases, since the interaction between the injected liquid and the components of the exhaust system can lead to the undesired formation of solid deposits. To avoid this, the thermal and kinematic interaction between the spray and the components of the after treatment system (ATS) must be modeled accurately. In this work, the authors developed a Conjugate Heat Transfer (CHT) framework to model the kinetic and thermal interaction among the spray, the eventual liquid layer and the pipe walls.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Numerous studies have demonstrated that exhaust gas recirculation (EGR) can attenuate knock propensity in spark ignition (SI) engines at naturally aspirated or lightly boosted conditions [1]. In this study, we investigate the role of cooled EGR under higher load conditions with multiple fuel compositions, where highly retarded combustion phasing typical of modern SI engines was used. It was found that under these conditions, EGR attenuation of knock is greatly reduced, where EGR doesn’t allow significant combustion phasing advance as it does under lighter load conditions. Detailed combustion analysis shows that when EGR is added, the polytropic coefficient increases causing the compressive pressure and temperature to increase. At sufficiently highly boosted conditions, the increase in polytropic coefficient and additional trapped mass from EGR can sufficiently reduce fuel ignition delay to overcome knock attenuation effects.

This study presents the development of a new HCCI simulation methodology. The proposed method is based on the sequential coupling of CFD analysis prior to autoignition, followed by multi-zone chemical kinetics analysis of the combustion process during the closed valve period. The methodology is divided into three steps: 1) a 1-zone chemical kinetic model (Chemkin Pro) is used to determine either the intake conditions at IVC to achieve a desired ignition timing or the ignition timing corresponding with given IVC conditions, 2) the ignition timing and IVC conditions are used as input parameters in a CFD model (Fluent 6.3) to calculate the charge temperature profile and mass distribution prior to autoignition, and 3) the temperature profile and mass distribution are fed into a multi-zone chemical kinetic model (Chemkin Pro) to determine the main combustion characteristics.

Compressed Natural Gas (CNG) has favorable characteristics as a vehicular fuel, in terms of fuel economy as well as emissions Using CNG as a fuel in a series hybrid vehicle has the potential of resulting in very high fuel economy (between 26 and 30 km/liter, 60 to 70 mpg) and very low emissions (substantially lower than Federal Tier II or CARB ULEV) This paper uses a vehicle evaluation code and an optimizer to find a set of vehicle parameters that result in optimum vehicle fuel economy The vehicle evaluation code used in this analysis estimates vehicle power train performance, including engine efficiency and power, generator efficiency, energy storage device efficiency and state-of-charge, and motor and transmission efficiencies Eight vehicle parameters are selected as free variables for the optimization The optimum vehicle must also meet three performance requirements accelerate to 97 km/h in less than 10 s, climb an infinitely long hill with a 6% slope at 97 km/h with a 272 kg (600 lb) payload, and have a 610 km (380 mile) range in the combined urban/highway driving cycle The optimizer used in this work was originally developed in the magnetic fusion energy program, and has been used to optimize complex systems, such as magnetic and inertial fusion devices, neutron sources, and rail guns The optimizer consists of two parts an optimization package for minimizing non-linear functions of many variables subject to several nonlinear equality and/or inequality constraints and a programmable shell that allows interactive configuration and execution of the optimizer The results of the analysis indicate that the CNG senes hybrid vehicle has a high fuel economy and low emissions These results emphasize the advantages of CNG as a near-term alternative fuel for vehicles

Hydrogen-fueled, spark-ignited, homogeneous-charge engines offer an alternative for providing Equivalent Zero Emission Vehicle (EZEV) levels, along with a range and performance comparable to today's automobiles. Hydrogen in a spark-ignited engine can be burned at very low equivalence ratios, so that NOx emissions can be reduced to less than 10 ppm without a catalytic converter or EGR. HC and CO emissions may result from oxidation of engine oil, but by proper design are negligible (a few ppm). Lean operation also results in increased indicated efficiency due to the thermodynamic properties of the gaseous mixture contained in the cylinder and due to reduced heat transfer. The high effective octane number of hydrogen allows the use of a high compression ratio, further increasing engine efficiency. In this paper, a time-dependent engine model is used for predicting hydrogen engine efficiency and emissions.

A Euro6 gasoline light duty vehicle has been tested at the engine dynamometer and the emissions have been analyzed upstream and downstream the Three-Way-Catalyst (TWC) during a WLTC cycle. Catalyst simulations have been used for assessing the processes inside the catalytic converter using a reaction scheme based on 19 brutto reactions (direct oxidation and reduction, selective catalytic reductions with CO, C3H6 and H2, steam reforming, water-gas shift and bulk ceria as well as surface ceria reactions). The reactions have been parameterized in order to best approximate the measurements. Based on the reactions taken into account, the real vehicle emissions can be predicted with good accuracy. The simulations show that the cycle emissions comprise mainly the cold start contribution as well as discrete emission break-through events during transients. During cold start no reactions are evident in the catalyst before the temperature of the gas entering the catalyst reaches 270°C.

The transient heat transfer behavior of an automotive catalytic converter has been simulated with OpenFOAM in 1D. The model takes into consideration the gas-solid convective heat transfer, axial wall conduction and heat capacity effects in the solid phase, but also the chemical reactions of CO oxidation, based on simplified Arrhenius and Langmuir-Hinshelwood approaches. The associated parameters are the results of data in literature tuned by experiments. Simplified cases of constant flow rates and gas temperatures in the catalyst inflow have been chosen for a comprehensive analysis of the heat and mass transfer phenomena. The impact of inlet flow temperatures and inlet flow rates on the heat up characteristics as well as in the CO emissions have been quantified. A dimensional analysis is proposed and dimensionless temperature difference and space-time coordinates are introduced.

The Computational Chemistry Consortium (C3) is dedicated to leading the advancement of combustion and emissions modeling. The C3 cluster combines the expertise of different groups involved in combustion research aiming to refine existing chemistry models and to develop more efficient tools for the generation of surrogate and multi-fuel mechanisms, and suitable mechanisms for CFD applications. In addition to the development of more accurate kinetic models for different components of interest in real fuel surrogates and for pollutants formation (NOx, PAH, soot), the core activity of C3 is to develop a tool capable of merging high-fidelity kinetics from different partners, resulting in a high-fidelity model for a specific application. A core mechanism forms the basis of a gasoline surrogate model containing larger components including n-heptane, iso-octane, n-dodecane, toluene and other larger hydrocarbons.

Laminar burning velocity (LBV) measurements are reported for promising high-performance fuels selected as drop-in transportation fuels to automotive grade gasoline as part of the United States Department of Energy’s Co-Optimization of Fuels and Engines Initiative (Co-Optima). LBV measurements were conducted for ethanol, methyl acetate, and 2-methylfuran with synthetic air (79.0 % N2 and 21.0 % O2 by volume) within a constant-volume spherical combustion rig. Mixture initial temperature was fixed at 428±4 K, with the corresponding initial pressure of 1.00±0.02 atm. Current LBV of ethanol is in good agreement with literature data. LBV of ethanol and 2-methylfuran showed similar values over the range of equivalence ratios, while methyl acetate exhibited an LBV significantly lower over the range of tested equivalence ratios. The maximum laminar burning velocity occurred at slightly richer equivalence ratio from the stoichiometric value for all fuels tested.

Remote emission sensing (RES) is a non-intrusive measurement method based on absorption spectroscopy, which allows for the determination of pollutant concentrations in vehicle exhaust plumes. By measuring the absorption of the exhaust plume from the roadside using a light/laser barrier, concentration ratios of pollutants, such as nitrogen oxides to carbon dioxide, can be estimated. Computational fluid dynamics (CFD) has been employed to simulate vehicle exhaust plumes due to uncertainties in RES capabilities. In a previous study, Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations were conducted to investigate the dispersion of vehicle exhaust plumes under various ambient/driving conditions and provide insights for RES applications. However, the accuracy of these simulations can be further improved. Therefore, this study focuses on enhancing the simulation accuracy by employing large eddy simulations (LES).