Mapping the Operation of the Miniature Combustion Aerosol Standard (Mini-CAST) Soot Generator

The Jing Ltd. miniature combustion aerosol standard (Mini-CAST) soot generator is a portable, commercially available burner that is widely used for laboratory measurements of soot processes. While many studies have used the Mini-CAST to generate soot with known size, concentration, and organic carbon fraction under a single or few conditions, there has been no systematic study of the burner operation over a wide range of operating conditions. Here, we present a comprehensive characterization of the microphysical, chemical, morphological, and hygroscopic properties of Mini-CAST soot over the full range of oxidation air and mixing N-2 flow rates. Very fuel-rich and fuel-lean flame conditions are found to produce organic-dominated soot with mode diameters of 10-60nm, and the highest particle number concentrations are produced under fuel-rich conditions. The lowest organic fraction and largest diameter soot (70-130nm) occur under slightly fuel-lean conditions. Moving from fuel-rich to fuel-lean conditions also increases the O:C ratio of the soot coatings from similar to 0.05 to similar to 0.25, which causes a small fraction of the particles to act as cloud condensation nuclei near the Kelvin limit (kappa similar to 0-10(-3)). Comparison of these property ranges to those reported in the literature for aircraft and diesel engine soots indicates that the Mini-CAST soot is similar to real-world primary soot particles, which lends itself to a variety of process-based soot studies. The trends in soot properties uncovered here will guide selection of burner operating conditions to achieve optimum soot properties that are most relevant to such studies.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Revision of a Liquid Fuel Airblast Atomizer and Installation of a Laser Extinction System for Measurement of Soot Produced During Liquid Fuel Combustion

Studying liquid fuel combustion is necessary to better design combustion systems. Through more efficient combustors and alternative fuels, it is possible to reduce greenhouse gases and harmful emissions. In particular, coal-derived and Fischer-Tropsch liquid fuels are of interest because, in addition to producing fewer emissions, they have the potential to drastically reduce the United States' dependence on foreign oil. Major academic research institutions like the Pennsylvania State University perform cutting-edge research in many areas of combustion. The Combustion Research Laboratory (CRL) at Bucknell University is striving to develop the necessary equipment to be capable of both independent and collaborative research efforts with Penn State and in the process, advance the CRL to the forefront of combustion studies. The focus of this thesis is to advance the capabilities of the Combustion Research Lab at Bucknell. Specifically, this was accomplished through a revision to a previously designed liquid fuel injector, and through the design and installation of a laser extinction system for the measurement of soot produced during combustion. The previous liquid fuel injector with a 0.005" hole did not behave as expected. Through spray testing the 0.005" injector with water, it was determined that experimental errors were made in the original pressure testing of the injector. Using data from the spray testing experiment, new theoretical hole sizes of the injector were calculated. New injectors with 0.007" and 0.0085" orifices were fabricated and subsequently tested to qualitatively validate their behavior. The injectors were installed in the combustion rig in the CRL and hot-fire tested with liquid heptane. The 0.0085" injector yielded a manageable fuel pressure and produced a broad flame. A laser extinction system was designed and installed in the CRL. This involved the fabrication of a number of custom-designed parts and the specification of laser extinction equipment for purchase. A standard operating procedure for the laser extinction system was developed to provide a consistent, safe method for measuring soot formation during combustion.