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.

Characterization of Halyomorpha halys (brown marmorated stink bug) biogenic volatile organic compound emissions and their role in secondary organic aerosol formation.

The formation of aerosols is a key component in understanding cloud formation in the context of radiative forcings and global climate modeling. Biogenic volatile organic compounds (BVOCs) are a significant source of aerosols, yet there is still much to be learned about their structures, sources, and interactions. The aims of this project were to identify the BVOCs found in the defense chemicals of the brown marmorated stink bug Halymorpha halys and quantify them using gas chromatography-mass spectrometry (GC/MS) and test whether oxidation of these compounds by ozone-promoted aerosol and cloud seed formation. The bugs were tested under two conditions: agitation by asphyxiation and direct glandular exposure. Tridecane, 2(5H)-furanone 5-ethyl, and (E)-2-decenal were identified as the three most abundant compounds. H. halys were also tested in the agitated condition in a smog chamber. It was found that in the presence of 100-180 ppm ozone, secondary aerosols do form. A scanning mobility particle sizer (SMPS) and a cloud condensation nuclei counter (CCNC) were used to characterize the secondary aerosols that formed. This reaction resulted in 0.23 microg/ bug of particulate mass. It was also found that these secondary organic aerosol particles could act as cloud condensation nuclei. At a supersaturation of 1%, we found a kappa value of 0.09. Once regional populations of these stink bugs stabilize and the populations estimates can be made, the additional impacts of their contribution to regional air quality can be calculated.

Characterization of Halyomorpha Halys (Brown Marmorated Stink Bug) Biogenic Volatile Organic Compound Emissions and Their Role in Secondary Organic Aerosol Formation

The formation of aerosols is a key component in understanding cloud formation in the context of radiative forcings and global climate modeling. Biogenic volatile organic compounds (BVOCs) are a significant source of aerosols, yet there is still much to be learned about their structures, sources, and interactions. The aims of this project were to identify the BVOCs found in the defense chemicals of the brown marmorated stink bug Halymorpha halys and quantify them using gas chromatography-mass spectrometry (GC/MS) and test whether oxidation of these compounds by ozone-promoted aerosol and cloud seed formation. The bugs were tested under two conditions: agitation by asphyxiation and direct glandular exposure. Tridecane, 2(5H)-furanone 5-ethyl, and (E)-2-decenal were identified as the three most abundant compounds. H. halys were also tested in the agitated condition in a smog chamber. It was found that in the presence of 100-180 ppm ozone, secondary aerosols do form. A scanning mobility particle sizer (SMPS) and a cloud condensation nuclei counter (CCNC) were used to characterize the secondary aerosols that formed. This reaction resulted in 0.23 mu g/bug of particulate mass. It was also found that these secondary organic aerosol particles could act as cloud condensation nuclei. At a supersaturation of 1%, we found a kappa value of 0.09. Once regional populations of these stink bugs stablilize and the populations estimates can be made, the additional impacts of their contribution to regional air quality can be calculated. Implications: Halymorpha halys (brown marmorated stink bugs) are a relatively new invasive species introduced in the United States near Allentown, Pennsylvania. The authors chemically speciated the bugs' defense pheromones and found that tridecane, 5-ethyl-2(5H)-furanone, and (E)-2-decenal dominated their emissions. Their defense emissions were reacted with atmospherically relevant concentrations of ozone and resulted in 0.23 g of particulate matter per emission per bug. Due to the large population of these bugs in some regions, these emissions could contribute appreciably to a region's PM2.5 (particulate matter with an aerodynamic diameter 2.5 m) levels.

Geochemical Modeling and Analysis of the Frac Water Used in the Hydraulic Fracturing of the Marcellus Formation, Pennsylvania

The hydraulic fracturing of the Marcellus Formation creates a byproduct known as frac water. Five frac water samples were collected in Bradford County, PA. Inorganic chemical analysis, field parameters analysis, alkalinity titrations, total dissolved solids(TDS), total suspended solids (TSS), biological oxygen demand (BOD), and chemical oxygen demand (COD) were conducted on each sample to characterize frac water. A database of frac water chemistry results from across the state of Pennsylvania from multiple sources was compiled in order to provide the public and research communitywith an accurate characterization of frac water. Four geochemical models were created to model the reactions between frac water and the Marcellus Formation, Purcell Limestone, and the oil field brines presumed present in the formations. The average concentrations of chloride and TDS in the five frac water samples were 1.1 �± 0.5 x 105 mg/L (5.5X average seawater) and 140,000 mg/L (4X average seawater). BOD values for frac water immediately upon flow back were over 10X greater than the BOD of typical wastewater, but decreased into the range of typical wastewater after a short period of time. The COD of frac water decreases dramatically with an increase in elapsed time from flow back, but remain considerably higher than typicalwastewater. Different alkalinity calculation methods produced a range of alkalinity values for frac water: this result is most likely due to high concentrations of aliphatic acid anions present in the samples. Laboratory analyses indicate that the frac watercomposition is quite variable depending on the companies from which the water was collected, the geology of the local area, and number of fracturing jobs in which the frac water was used, but will require more treatment than typical wastewater regardless of theprecise composition of each sample. The geochemical models created suggest that the presence of organic complexes in an oil field brine and Marcellus Formation aid in the dissolution of ions such as bariumand strontium into the solution. Although equilibration reactions between the Marcellus Formation and the slickwater account for some of the final frac water composition, the predominant control of frac water composition appears to be the ratio of the mixture between the oil field brine and slickwater. The high concentration of barium in the frac water is likely due to the abundance of barite nodules in the Purcell Limestone, and the lack of sulfate in the frac water samples is due to the reducing, anoxic conditions in the earth's subsurface that allow for the degassing of H2S(g).