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Selective Catalytic Reduction (SCR) catalysts are used to reduce NOx emissions from internal combustion engines in a variety of applications [1,2,3,4]. Southwest Research Institute (SwRI) performed an Internal Research & Development project to study SCR catalyst thermal deactivation. The study included a V/W/TiO2 formulation, a Cu-zeolite formulation and a Fe-zeolite formulation. This work describes NH3 storage capacity measurement data as a function of aging time and temperature. Addressing one objective of the work, these data can be used in model-based control algorithms to calculate the current NH3 storage capacity of an SCR catalyst operating in the field, based on time and temperature history. The model-based control then uses the calculated value for effective DEF control and prevention of excessive NH3 slip. Addressing a second objective of the work, accelerated thermal aging of SCR catalysts may be achieved by elevating temperatures above normal operating temperatures.

The Hybrid Electric Vehicle Team of Virginia Tech participated in the three-year EcoCAR Advanced Vehicle Technology Competition organized by Argonne National Laboratory, and sponsored by General Motors and the U.S. Department of Energy. The team established goals for the design of a plug-in, range-extended hybrid electric vehicle that meets or exceeds the competition requirements for EcoCAR. The challenge involved designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use, regulated tailpipe emissions, and well-to-wheel greenhouse gas emissions. To interface with and control the hybrid powertrain, the team added a Hybrid Vehicle Supervisory Controller, which enacts a torque split control strategy. This paper builds on an earlier paper [1] that evaluated the petroleum energy use, criteria tailpipe emissions, and greenhouse gas emissions of the Virginia Tech EcoCAR vehicle and control strategy from the 2nd year of the competition.

In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

Ammonia/urea-SCR is a mature technology, applied worldwide for the control of NOx emissions in combustion exhausts from thermal power plants, cogeneration units, incinerators and stationary diesel engines and more recently also from mobile sources. However a greater DeNOx activity at low temperatures is desired in order to meet more and more restrictive legislations. In this paper we report transient and steady state data collected over commercial Fe-ZSM-5 and V₂O₅-WO₃/TiO₂ catalysts showing high NOx reduction efficiencies in the 200 - 350°C T-range when NO and ammonia react with nitrates, e.g., in the form of an aqueous solution of ammonium nitrate. Under such conditions a new reaction occurs, the so-called "Enhanced SCR" reaction, 2 NH₃ + 2 NO + NH₄NO₃ → 3 N₂ + 5 H₂O.

Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.

Response surface methodology (RSM) techniques were applied to develop a predictive model of electric vehicle (EV) energy consumption over the Environmental Protection Agency's (EPA) standardized drive cycles. The model is based on measurements from a synthetic composite drive cycle. The synthetic drive cycle is a minimized statistical composite of the standardized urban (UDDS), highway (HWFET), and US06 cycles. The composite synthetic drive cycle is 20 minutes in length thereby reducing testing time of the three standard EPA cycles by over 55%. Vehicle speed and acceleration were used as model inputs for a third order least squared regression model predicting vehicle battery power output as a function of the drive cycle. The approach reduced three cycles and 46 minutes of drive time to a single test of 20 minutes.

Detailed chemistry and turbulence-chemistry interaction need to be properly taken into account for a realistic combustion simulation of IC engines where advanced combustion modes, multiple injections and stratified combustion involve a wide range of combustion regimes and require a proper description of several phenomena such as auto-ignition, flame stabilization, diffusive combustion and lean premixed flame propagation. To this end, different approaches are applied and the most used ones rely on the well-stirred reactor or flamelet assumption. However, well-mixed models do not describe correctly flame structure, while unsteady flamelet models cannot easily predict premixed flame propagation and triple flames. A possible alternative for them is represented by transported probability density functions (PDF) methods, which have been applied widely and effectively for modeling turbulent reacting flows under a wide range of combustion regimes.

Cavitation plays a significant role in high pressure diesel injectors. However, cavitation is difficult to measure under realistic conditions. X-ray phase contrast imaging has been used in the past to study the internal geometry of fuel injectors and the structure of diesel sprays. In this paper we extend the technique to make in-situ measurements of cavitation inside unmodified diesel injectors at pressures of up to 1200 bar through the steel nozzle wall. A cerium contrast agent was added to a diesel surrogate, and the changes in x-ray intensity caused by changes in the fluid density due to cavitation were measured. Without the need to modify the injector for optical access, realistic injection and ambient pressures can be obtained and the effects of realistic nozzle geometries can be investigated. A range of single and multi-hole injectors were studied, both sharp-edged and hydro-ground. Cavitation was observed to increase with higher rail pressures.

Low temperature combustion through in-cylinder blending of fuels with different reactivity offers the potential to improve engine efficiency while yielding low engine-out NOx and soot emissions. A Navistar MaxxForce 13 heavy-duty compression ignition engine was modified to run with two separate fuel systems, aiming to utilize fuel reactivity to demonstrate a technical path towards high engine efficiency. The dual-fuel engine has a geometric compression ratio of 14 and uses sequential, multi-port-injection of a low reactivity fuel in combination with in-cylinder direct injection of diesel. Through control of in-cylinder charge reactivity and reactivity stratification, the engine combustion process can be tailored towards high efficiency and low engine-out emissions. Engine testing was conducted at 1200 rpm over a load sweep.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

In the next years, the upcoming emission legislations are expected to introduce further restrictions on the admittable level of pollutants from vehicles measured on homologation cycles and real drive tests. In this context, the strict control of pollutant emissions at the cold start will become a crucial point to comply with the new regulation standards. This will necessarily require the implementation of novel strategies to speed-up the light-off of the reactions occurring in the after-treatment system, since the cold start conditions are the most critical one for cumulative emissions. Among the different possible technological solutions, this paper focuses on the evaluation of the potential of a burner system, which is activated before the engine start. The hypothetical burner exploits the lean combustion of an air-gasoline mixture to generate a high temperature gas stream which is directed to the catalyst section promoting a fast heating of the substrate.

Modeling combustion of transportation fuels remains a difficult task due to the extremely large number of species constituting commercial gasoline and diesel. However, for this purpose, multi-component surrogate fuel models with a reduced number of key species and dedicated reaction subsets can be used to reproduce the physical and chemical traits of diesel and gasoline, also allowing to perform CFD calculations. Recently, a detailed surrogate fuel kinetic model, named C3 mechanism, was developed by merging high-fidelity sub-mechanisms from different research groups, i.e. C0-C4 chemistry (NUI Galway), linear C6-C7 and iso-octane chemistry (Lawrence Livermore National Laboratory), and monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) (ITV-RWTH Aachen and CRECK modelling Lab-Politecnico di Milano).

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

Quantitative measurements of direct injection fuel spray density and mixing are difficult to achieve using optical diagnostics, due to the substantial scattering of light and high optical density of the droplet field. For multi-hole sprays, the problem is even more challenging, as it is difficult to isolate a single spray plume along a single line of sight. Time resolved x-ray radiography diagnostics developed at Argonne's Advanced Photon Source have been used for some time to study diesel fuel sprays, as x-rays have high penetrating power in sprays and scatter only weakly. Traditionally, radiography measurements have been conducted along any single line of sight, and have been applied to single-hole and group-hole nozzles with few plumes. In this new work, we extend the technique to multi-hole gasoline direct injection sprays.

Interest in natural gas as an alternative fuel source to petroleum fuels for light-duty vehicle applications has increased due to its domestic availability and stable price compared to gasoline. With its higher hydrogen-to-carbon ratio, natural gas has the potential to reduce engine out carbon dioxide emissions, which has shown to be a strong greenhouse gas contributor. For part-load conditions, the lower flame speeds of natural gas can lead to an increased duration in the inflammation process with traditional port-injection. Direct-injection of natural gas can increase in-cylinder turbulence and has the potential to reduce problems typically associated with port-injection of natural gas, such as lower flame speeds and poor dilution tolerance. A study was designed and executed to investigate the effects of direct-injection of natural gas at part-load conditions.

Fuel lean combustion and exhaust gas dilution are known to increase the thermal efficiency and reduce NOx emissions. In this study, experiments are performed to understand the effect of equivalence ratio on flame kernel formation and flame propagation around the spark plug for different low turbulent velocities. A series of experiments are carried out for propane-air mixtures to simulate engine-like conditions. For these experiments, equivalence ratios of 0.7 and 0.9 are tested with 20 percent mass-based exhaust gas recirculation (EGR). Turbulence is generated by a shrouded fan design in the vicinity of J-spark plug. A closed loop feedback control system is used for the fan to generate a consistent flow field. The flow profile is characterized by using Particle Image Velocimetry (PIV) technique. High-speed Schlieren visualization is used for the spark formation and flame propagation.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The importance of radiative heat transfer on the combustion and soot formation characteristics under nominal ECN Spray A conditions has been studied numerically. The liquid n-dodecane fuel is injected with 1500 bar fuel pressure into the constant volume chamber at different ambient conditions. Radiation from both gas-phase as well as soot particles has been included and assumed as gray. Three different solvers for the radiative transfer equation have been employed: the discrete ordinate method, the spherical-harmonics method and the optically thin assumption. The radiation models have been coupled with the transported probability density function method for turbulent reactive flows and soot, where unresolved turbulent fluctuations in temperature and composition are included and therefore capturing turbulence-chemistry-soot-radiation interactions. Results show that the gas-phase (mostly CO2 ad H2O species) has a higher contribution to the net radiation heat transfer compared to soot.

Metallic foams or sponges are materials with a cell structure suitable for many industrial applications, such as reformers, heat catalytic converters, etc. The success of these materials is due to the combination of various characteristics such as mechanical strength, low density, high specific surface, good thermal exchange properties, low flow resistance and sound absorption. Different materials and manufacturing processes produce different type of structure and properties for various applications. In this work a genetic algorithm has been developed and applied to support the design of catalytic devices. In particular, two substrates were considered, namely the traditional honeycomb and an alternative open-cell foam type. CFD simulations of pressure losses and literature based correlations for the heat and mass transfer were used to support the genetic algorithm in finding the best compromise between flow resistance and pollutant abatement.