Semester

Summer

Date of Graduation

2005

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Abstract

Emissions from heavy-duty diesel vehicles are known to contribute a substantial fraction of the oxides of nitrogen (NOx), and particulate matter (PM) to the atmospheric inventory. Prediction of heavy-duty diesel vehicle emissions inventory is substantially less mature than the prediction of gasoline car emissions.;Heavy-duty truck emissions are affected by various parameters like vehicle weight/load, driving schedule used, and injection timing control strategies employed to operate the engine at more fuel-efficient (but higher NO x) mode.;Research has revealed a variety of options for inventory prediction, including the use of emissions factors based upon instantaneous engine power and instantaneous vehicle behavior. Effects of various parameters on the heavy-duty diesel emissions were studied in great detail and a speed-acceleration based emissions prediction approach was developed for heavy-duty diesel vehicle emissions prediction. A suite of emissions factor tables was generated for emissions inventory prediction. Driving schedules, vehicle weight, and off-cycle injection strategy were found to affect emissions to varying extents. Detailed analyses of a large body of data enabled to quantitatively as well as qualitatively characterize effect of various parameters on heavy duty diesel vehicle emissions. A doubling of vehicle weight was found to result in roughly a 50% increase in NOx emissions. The accuracy was found to improve with the inclusion of a large number of data covering wide range of model year groups and driving schedules.;Off-cycle operation was found to increase the NOx emissions by more than double. The speed-acceleration model predicted the emissions with reasonable accuracy.

Download

Share

COinS