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An optical-based sensor for detecting particulate matter (PM) in diesel engine exhaust has been demonstrated. The position of the sensor during the experiments was the exhaust manifold prior to the turbocharger. The sensor is constructed of fiber optics which transmit 532-nm laser light into the exhaust pipe and collect backscattered light in a 180° geometry. Due to the optical nature of the probe, PM sensing can occur at high temporal rates. Experiments conducted by changing the fuel injection properties of one cylinder of a four cylinder engine demonstrated that the sensor can resolve cycle dependent events. The feasibility of the probe for examining PM emissions in the exhaust manifold will be discussed.

The 3-Zones Extended Coherent Flame Model (ECFM3Z) and the Tabulated Kinetics for Ignition (TKI) auto-ignition model are widely used for RANS simulations of reactive flows in Diesel engines. ECFM3Z accounts for the turbulent mixing between one zone that contains compressed air and EGR and another zone that contains evaporated fuel. These zones mix to form a reactive zone where combustion occurs. In this mixing zone TKI is applied to predict the auto-ignition event, including the ignition delay time and the heat release rate. Because it is tabulated, TKI can model complex fuels over a wide range of engine thermodynamic conditions. However, the ECFM3Z/TKI combustion modeling approach requires an efficient predictive spray injection calculation. In a Diesel direct injection engine, the turbulent mixing and spray atomization are mainly driven by the liquid/gas coupling phenomenon that occurs at moving liquid/gas interfaces.

A modified Mercedes 1.7-liter, direct-injection diesel engine was operated in both normal and high-efficiency clean combustion (HECC) combustion modes. Four steady-state engine operating points that were previously identified by the Ad-hoc fuels working group were used as test points to allow estimation of the hot-start FTP-75 emissions levels in both normal and HECC combustion modes. The results indicate that operation in HECC modes generally produce reductions in NOX and PM emissions at the expense of CO, NMHC, and H2CO emissions. The FTP emissions estimates indicate that aftertreatment requirements for NOX are reduced, while those for PM may not be impacted. Cycle-average aftertreatment requirements for CO, NMHC, and H2CO may be challenging, especially at the lowest temperature conditions.

A hybrid LNT+SCR system is used to control NOx from a light-duty diesel engine with in-cylinder regeneration controls. A diesel oxidation catalyst and diesel particulate filter are upstream of the LNT and SCR catalysts. Ultraviolet (UV) adsorption spectroscopy performed directly in the exhaust path downstream of the LNT and SCR catalysts is used to characterize NH3 production and utilization in the system. Extractive exhaust samples are analyzed with FTIR and magnetic sector mass spectrometry (H2) as well. Furthermore, standard gas analyzers are used to complete the characterization of exhaust chemistry. NH3 formation increases strongly with extended regeneration (or “over regeneration”) of the LNT, but the portion of NOx reduction occurring over the SCR catalyst is limited by the amount of NH3 produced as well as the amount of NOx available downstream of the LNT. Control of lean-rich cycling parameters enables control of the ratio of NOx reduction between the LNT and SCR catalysts.

A commercial three-way catalyst (TWC) was evaluated for ammonia (NH3) generation on a 2.0-liter BMW lean burn gasoline direct injection engine as a component in a passive ammonia selective catalytic reduction (SCR) system. The passive NH3 SCR system is a potential low cost approach for controlling nitrogen oxides (NOX) emissions from lean burn gasoline engines. In this system, NH3 is generated over a close-coupled TWC during periodic slightly rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst. NH3 generation was evaluated at different air-fuel equivalence ratios at multiple engine speed and load conditions. Near complete conversion of NOX to NH3 was achieved at λ=0.96 for nearly all conditions studied. At the λ=0.96 condition, HC emissions were relatively minimal, but CO emissions were significant.

Lean gasoline engines offer greater fuel economy than the common stoichiometric gasoline engine, but the current three way catalyst (TWC) on stoichiometric engines is unable to control nitrogen oxide (NOX) emissions in oxidizing exhaust. For these lean gasoline engines, lean NOX emission control is required to meet existing Tier 2 and upcoming Tier 3 emission regulations set by the U.S. Environmental Protection Agency (EPA). While urea-based selective catalytic reduction (SCR) has proven effective in controlling NOX from diesel engines, the urea storage and delivery components can add significant size and cost. As such, onboard NH3 production via a passive SCR approach is of interest. In a passive SCR system, NH3 is generated over a close-coupled TWC during periodic slightly rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean operation, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst.

The widespread adoption of boosted, downsized SI engines has brought pre-ignition phenomena into greater focus, as the knock events resulting from pre-ignitions can cause significant hardware damage. Much attention has been given to understanding the causes of pre-ignition and identify lubricant or fuel properties and engine design and calibration considerations that impact its frequency. This helps to shift the pre-ignition limit to higher specific loads and allow further downsizing but does not fundamentally eliminate the problem. Real-time detection and mitigation of pre-ignition would thus be desirable to allow safe engine operation in pre-ignition-prone conditions. This study focuses on advancing the time of detection of pre-ignition in an engine cycle where it occurs.

Detailed chemical kinetics, although preferred due to increased accuracy, can significantly slow down CFD combustion simulations. Chemistry solutions are typically the most computationally costly step in engine simulations. The calculation time can be significantly accelerated using a multi-zone combustion model. The multi-zone model is integrated into the CONVERGE CFD code. At each time-step, the CFD cells are grouped into zones based on the cell temperature and equivalence ratio. The chemistry solver is invoked only on each zone. The zonal temperature and mass fractions are remapped onto the CFD cells, such that the temperature and composition non-uniformities are preserved. Two remapping techniques published in the literature are compared for their relative performance. The accuracy and speed-up of the multi-zone model is improved by using variable bin sizes at different temperature and equivalence ratios.

Thermal conductivity detection has long been used in gas chromatography to detect hydrogen and other diatomic gases in a gas sample. Thermal conductivity instruments that are not coupled to gas chromatographs are useful for detecting hydrogen in binary gas mixtures, but suffer from significant cross-interference from other gas species that are separated when the detector is used with a gas chromatograph. This study reports a method for using a commercially-available thermal conductivity instrument to detect and quantify hydrogen in a diesel exhaust stream. The instrument time response of approximately 40 seconds is sufficient for steady-state applications. Cross-interference from relevant gas species are quantified and discussed. Measurement uncertainty associated with the corrections for the various species is estimated and practical implications for use of the instrument and method are discussed.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

This project team conducted a life-cycle-based environmental evaluation of new, lightweight materials (e.g., titanium, magnesium) used in two concept 3XVs -- i.e., automobiles that are three times more fuel efficient than today's automobiles -- that are being designed and developed in support of the Partnership for a New Generation of Vehicles (PNGV) program. The two concept vehicles studied were the DaimlerChrysler ESX2 and the Ford P2000. Data for this research were drawn from a wide range of sources, including: the two automobile manufacturers; automobile industry reports; government and proprietary databases; past life-cycle assessments; interviews with industry experts; and models.

Internal combustion engines are operated under conditions of high exhaust gas recirculation (EGR) to reduce NOx emissions and promote enhanced combustion modes such as HCCI. However, high EGR under certain conditions also promotes nonlinear feedback between cycles, leading to the development of combustion instabilities and cyclic variability. We employ a two-zone phenomenological combustion model to simulate the onset of combustion instabilities under highly dilute conditions and to illustrate the impact of these instabilities on emissions and fuel efficiency. The two-zone in-cylinder combustion model is coupled to a WAVE engine-simulation code through a Simulink interface, allowing rapid simulation of several hundred successive engine cycles with many external engine parametric effects included.

One scenario for reducing engine out NOx in a spark ignition engine is to introduce small amounts of supplemental hydrogen to the combustion process. The supplemental hydrogen enables a gasoline engine to run lean where NOx emissions are significantly reduced and engine efficiency is increased relative to stoichiometric operation. This paper reports on a mass and energy balance model that has been developed to evaluate the overall system efficiencies of a thermal reformer-heat exchanger system capable of delivering hydrogen to the air intake of a gasoline engine. The mass and energy balance model is utilized to evaluate the conditions where energy losses associated with fuel reformation may be offset by increases in engine efficiencies.

While gasoline surrogate development has progressed in the areas of more complex surrogate mixtures and in kinetic modeling tools and mechanism development, it is generally recognized that further development is still needed. This paper represents a small step in supporting this development by providing comparisons between experimental engine data and surrogate-based kinetic models. In our case, the HCCI engine data comes from a port-injected, single-cylinder research engine with intake-air heating for combustion phasing control. Timing sweeps were run at constant fuel rate for three market gasolines and five surrogate mixtures. Modeling was done using the CHEMKIN software with a gasoline mechanism set containing 1440 species and 6572 reactions. Five pure compounds were selected for the surrogate blends and include iso-octane, n-heptane, toluene, methylcyclohexane, and 1-hexene.