Search Results

Knock is a major bottleneck to achieving higher thermal efficiency in spark ignition (SI) engines. The overall tendency to knock is highly dependent on fuel anti-knock quality as well as engine operating conditions. It is, therefore, critical to gain a better understanding of fuel-engine interactions in order to develop robust knock mitigation strategies. In the present work, a numerical model based on three-dimensional (3-D) computational fluid dynamics (CFD) was developed to capture knock in a Cooperative Fuel Research (CFR) engine. For combustion modeling, a hybrid approach incorporating the G-equation model to track turbulent flame propagation, and a homogeneous reactor multi-zone model to predict end-gas auto-ignition ahead of the flame front and post-flame oxidation in the burned zone, was employed.

The CFR engine is the widely accepted platform to test standard Research Octane Number (RON) and Motored Octane Number (MON) for determining anti-knock characteristics of motor fuels. With increasing interest in engine downsizing, up-torquing, and alternative fuels for modern spark ignition (SI) engines, there is a need to better understand the conditions that fuels are subjected to in the CFR engine during octane rating. To take into account fuel properties, such as fuel heat of vaporization, laminar flame speed and auto-ignition chemistry; and understand their impacts on combustion knock, it is essential to estimate accurate cylinder conditions. In this study, the CFR F1/F2 engine was modeled using GT-Power with the Three Pressure Analysis (TPA) and the model was validated for different fuels and engine conditions.

Mobile source emissions standards are becoming more stringent and particulate emissions from gasoline direct injection (GDI) engines represent a particular challenge. Gasoline particulate filter (GPF) is deemed as one possible technical solution for particulate emissions reduction. In this work, a study was conducted on eight formulations of lubricants to determine their effect on GDI engine particulate emissions and GPF performance. Accelerated ash loading tests were conducted on a 2.4L GDI engine with engine oil injection in gasoline fuel by 2%. The matrix of eight formulations was designed with changing levels of sulfated ash (SASH) level, Zinc dialkyldithiophosphates (ZDDP) level and detergent type. Comprehensive evaluations of particulates included mass, number, size distribution, composition, morphology and soot oxidation properties. GPF performance was assessed through filtration efficiency, back pressure and morphology.

Detailed characteristics of particulate matter (PM) from a gasoline-direct-injection (GDI) engine were analyzed in terms of primary and aggregate particle sizes, morphology, and nanostructures. For the work, PM was collected from exhaust streams of the engine on transmission electron microscope (TEM) grids by using a thermophoretic sampler. To evaluate the effects of engine load and speed on the properties of PM, the engine was operated at loads of 25, 50, and 75% at 1500 and 3000 rpm. In addition, the effects of fuel injection timing on the PM were examined for samples subjected to injection timings of 190, 230, 260, 300 and 330° bTDC at the constant engine load (50% load) and speed (1500 rpm). The results showed that with advancing injection timing, average primary and aggregate particle sizes gradually increased, which implies that fuel-air mixing is a crucial factor influencing particle size.

Detailed properties of particulate matter (PM) emissions from a gasoline direct injection (GDI) engine were analyzed in terms of size, morphology, and nanostructures, as gasoline and its ethanol blend E20 were used as a fuel. PM emissions were sampled from a 0.55L single-cylinder GDI engine by means of a scanning mobility particle sizer (SMPS) for size measurements and a self-designed thermophoretic sampling device for the subsequent analyses of size, morphology and nanostructures using a transmission electron microscope (TEM). The particle sizes were evaluated with variations of air-fuel equivalence ratio and fuel injection timing. The most important result from the SMPS measurements was that the number of nucleation-mode nanoparticles (particularly those smaller than 10 - 15 nm) increased significantly as the fuel injection timing was advanced to the end-of-injection angle of 310° bTDC.

A three-dimensional (3-D) computational fluid dynamics (CFD) code has been developed to predict flow dynamics and pressure drop characteristics in geometry-modified filters in which the normalized distance of the outlet channel plugs from the inlet has been varied at 0.25, 0.50, and 0.75. In clean filter simulations, the pressure drop in geometry-modified filters showed higher values than for conventional filters because of the significant change in the pressure field formed inside the channel that determines the amount of flow entering the modified channel. This flow through the modified channel depends on plug position initially but has a maximum limit when pressure difference and geometrical change are compromised. For soot loading simulations, a Lagrangian multiphase flow model was used to interpret the hydrodynamics of particle-laden flow with realistic inputs.

Detailed soot deposition and oxidation characteristics in a diesel particulate filter (DPF) have been experimentally examined on a unique bench-scale DPF test system that has a visualization window. The filtration and regeneration processes were visualized to examine soot deposition and oxidation behaviors on the filter channel surfaces, along with measurements of pressure drop across the filter. The pressure drop caused by trapped soot was separated from the measured total pressure drop by subtracting the pressure drop caused by the clean filter itself. Then, the soot-derived pressure-drop data, normalized (non-dimensionalized) by the volumetric flow rate, exhaust gas viscosity, and DPF volume, were used to compare filtration and regeneration characteristics at different experimental conditions, independently of flow conditions.

Detailed characteristics of morphology, nanostructures, and sizes were analyzed for particulate matter (PM) emissions from low-temperature combustion (LTC) modes of a single-cylinder, light-duty diesel engine. The LTC engines have been widely studied in an effort to achieve high combustion efficiency and low exhaust emissions. Recent reports indicate that the number of nucleation mode particles increased in a broad engine operating range, which implies a negative impact on future PM emissions regulations in terms of the nanoparticle number. However, the size measurement of solid carbon particles by commercial instruments is indeed controversial due to the contribution of volatile organics to small nanoparticles. In this work, an LTC engine was operated with various biofuel blends, such as blends (B20) of soy bean oil (soy methyl ester, SME20) and palm oil (palm methyl ester, PME20), as well as an ultra-low-sulfur diesel fuel.

The limited spatial area in conventional diesel particulate filter (DPF) systems requires frequent regenerations to remove collected particulate matter (PM) emissions, consequently resulting in higher energy consumption and potential material failure. Due to the complex geometry and difficulty in access to the internal structure of diesel particulate filters, in addition, many important characteristics in filtration processes remain unknown. In this work, therefore, the geometry of DPF membrane channels was modified basically to increase the filtration areas, and their filtration characteristics were evaluated in terms of pressure drop across the DPF membranes, effects of soot loading on pressure drop, and qualitative soot mass distribution in the membrane channels. In this evaluation, an analytical model was developed for pressure drop, which allowed a parametric study with those modified membranes.

This experimental work focuses on defining the detailed morphology of secondary emission products derived from the combustion of cerium (Ce) fuel-borne catalyst (FBC) doped with diesel fuel. Cerium is often used to promote the oxidation of diesel particulates collected in diesel aftertreatment systems, such as diesel particulate filters (DPFs). However, it is suspected that the secondary products could be emitted from the vehicle tailpipe without being effectively filtered by the aftertreatment systems. In this work, these secondary emissions were identified by means of a high-resolution transmission electron microscope (TEM), and their properties were examined in terms of morphology and chemistry. In preparation for fuel doping, a cerium-based aliphatic organic compound solution was mixed with a low-sulfur (110 ppm) diesel fuel at 50 ppm in terms of weight concentration.

Detailed diesel particulates morphology, nanostructures, fractal geometry, and nitrogen oxides (NOx) emissions were analyzed for five different test fuels in a 1.7-L, common-rail direct-injection diesel engine. The accurately formulated fuels permit the effects of sulfur, paraffins, aromatics, and naphthene concentrations to be determined. A novel thermophoretic sampling technique was used to collect particulates immediately after the exhaust valves. The morphology and nanostructures of particulate samples were examined, imaged with a high-resolution transmission electron microscope (HRTEM), and quantitatively analyzed with customized digital image processing/data acquisition systems. The results show that the particle sizes and the total mass of particulate matter (PM) emissions correlate most strongly with the fuels' aromatics and sulfur content.

This paper describes the initial experiments and computational simulations aimed to measure and quantify the level of nano-sized particulate production from combustion in low temperature combustion (LTC). This work measures nano-sized particles in a laminar ethylene flame both by the use of small-angle x-ray scattering at the Advanced Photon Source and through a technique called thermophoretic sampling. Future experiments will perform similar measurements in a Rapid Compression Machine under conditions typical for HCCI engines. The simulation work involves the use of coupled Computational Fluid Dynamics (CFD) and Chemistry Kinetics codes to predict the fuel/air mixture composition and temperature distribution in the combustion region and directly complements the experimental work. The results show that nano-particles are created under rich, premixed conditions, even with low temperature reactions (T<2000K).