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|Title: ||Assessment of On-Board Emissions and Energy Use of Nonroad Construction Vehicles|
|Authors: ||Abolhasani, Saeed|
|Advisors: ||Dr. H. Christopher Frey, Committee Chair|
Dr. M. Nagui Rouphail, Committee Member
Dr. Donald Van der vaart, Committee Member
|Issue Date: ||14-Nov-2006|
|Discipline: ||Civil Engineering|
|Abstract: ||In the past decade, nonroad engine emissions have increasingly become the focus of regulatory actions and air quality improvement strategies. The U.S. Environmental Protection Agency is undertaking an effort to develop a new set of modeling tools for estimation of emissions produced by nonroad vehicles. A critical element of the new models is the use of data gathered using on-board emissions measurement systems. Recent developments in on-board instrumentation enable measurement of vehicle activity and emissions under real- world conditions as opposed to laboratory tests.
The primary purpose of this thesis is to develop methodologies for on-board vehicle activity and emissions data collection, screening, and analysis for construction vehicles. The method was applied to field data collection for three excavators. Analysis of on-board data provided insights regarding quantification of variability in vehicle emissions and fuel consumption data. The influence of vehicle activity patterns on the average emission and fuel consumption rates was characterized using engine manifold absolute pressure. A consistent finding is that NO and CO2 emissions are highly correlated to fuel consumption, reflected in an average coefficient of determination of 0.96 between either of these emission rates and fuel consumption rate. Short-term episodes can produce a substantial portion of total emissions. For example, on average, 50% of the total NO emissions were associated with 28% of the time of vehicle operation, during which the average engine speed and manifold absolute pressure were significantly higher than corresponding averages for the total data.
A secondary, but equally important, purpose was to demonstrate a conceptual analytical methodology for analyzing on-board emissions data from nonroad construction vehicles and develop conceptual models to predict emissions using on-board data. Several different modeling methods were explored, including stratification of the data into operating modes, supplementing the modal models with ordinary least square regression, and multiple least squares regression. The modal approach offers the advantages of being conceptually the simplest, reducing the influence of autocorrelation in the model, and offering substantial explanatory power. The relationship between predicted mode-specific average emissions and exhaust flow was found to be stable, similar, and consistent for all vehicles. On average, an improvement in coefficient of determination value from 0.85 to 0.93 was estimated for observed versus estimated NOx emissions using combined-regression modal versus simple modal approach. Modal models can be used in a new set of modeling tools to estimate emissions produced by nonroad construction vehicles.|
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