Dissertations and Theses @ UNI
Availability
Open Access Dissertation
Keywords
Diesel motor exhaust gas -- Analysis; Diesel motor exhaust gas -- Measurement; Detectors;
Abstract
The study assessed the ability of a novel particle sensor to provide adequate evaluation of real-time emissions from modem diesel engines and estimate the effectiveness of emission control devices. Emission data were obtained from vehicles in real-world field conditions under various test cycles. The datasets were used to determine whether there is an association between particulate matter (PM) measurements produced by particle sensor and the PM measurements from reference instrument. Exploratory analysis was combined with statistical techniques to investigate suitability of particle sensor to adequately measure PM mass concentrations in exhaust gases of modem diesel vehicles. Results of the study identified strong positive association between measurements from particle sensor and reference instrument. Study confirmed the suitability of the sensor in the field to measure PM emissions of diesel vehicles. These findings are useful to researchers and governmental agencies involved in regulation, control, and monitoring of diesel engine emissions.
Year of Submission
2012
Degree Name
Doctor of Industrial Technology
Department
Department of Technology
First Advisor
Shahram VarzaVand
Second Advisor
Scott Giese
Date Original
2012
Object Description
1 PDF file (210 pages)
Copyright
©2012 Svetlana Korotkova Espinosa
Language
en
File Format
application/pdf
Recommended Citation
Espinosa, Svetlana Korotkova, "Limited assessment of a selected particulate matter sensor technology in emission measurement applications on diesel vehicles" (2012). Dissertations and Theses @ UNI. 1264.
https://scholarworks.uni.edu/etd/1264
Comments
If you are the rightful copyright holder of this dissertation or thesis and wish to have it removed from the Open Access Collection, please submit a request to scholarworks@uni.edu and include clear identification of the work, preferably with URL.