Improving Remote Sensing of Vehicle Emissions through Monitoring Data, Vehicle Fault Analysis and Tailpipe Temperature Setting

Organ, Bruce Douglas

Improving Remote Sensing of Vehicle Emissions through Monitoring Data, Vehicle Fault Analysis and Tailpipe Temperature Setting

Organ, Bruce Douglas

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Publication Type:: Thesis
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Organ, Bruce Douglas
dc.date.accessioned	2022-10-14T02:20:06Z
dc.date.available	2022-10-14T02:20:06Z
dc.date.issued	2022
dc.identifier.uri	http://hdl.handle.net/10453/162586
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Air pollution is a serious public health issue around the globe that needs to be addressed. Pollution from vehicle transport emissions is a significant component of this problem and pollution control programmes have not been able to satisfactorily reduce this. Since traditional controls are not sufficient to reduce vehicle emissions, the application of non-intrusive Remote Sensing (RS) of vehicle emissions can make a difference. Since 2014, RS has been deployed by the Hong Kong Environmental Protection Department to identify Gasoline and Liquified Petroleum Gas fuelled vehicles excessively emitting pollutants. The assessment of the effectiveness of this RS system application by investigating the data from this programme has been undertaken. The analysis of five years of RS data from January 2012 to December 2016 showed that by 2016 that there were significant reductions of Emissions Factors ranging between 29.6% to 58.7% for HC, CO and NO. Such results highlighted that utilising RS is effectively helping to reduce vehicle emissions and improve air quality. To improve emissions failure knowledge in the automotive repair industry and in turn their capability to identify and rectify emissions problems in vehicles, a demonstration taxi with relevant engine hardware was used to simulate 15 different faults. Testing showed these faults could increase emissions by up to 317%, 782% and 282% for HC, CO and NOx respectively. The knowledge developed from this was used to educate the repair industry on the largest emissions fault sources so effective repairs could be performed. To assess RS measurement variability, calibration devices were built and tested. These identified that the temperature of exhaust gas being measured impacted the RS measurement results. To improve RS reliability, such measurements should occur 50 cm away from the exhaust tailpipe which helps reduce temperature related variability. Applying this will help to improve RS measurement accuracy, with an aim to make RS effective for all types of vehicles regardless of fuel or their size.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/162586/2/02whole.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	au.edu.uts.lib/ppc
dc.title	Improving Remote Sensing of Vehicle Emissions through Monitoring Data, Vehicle Fault Analysis and Tailpipe Temperature Setting	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Air pollution is a serious public health issue around the globe that needs to be addressed. Pollution from vehicle transport emissions is a significant component of this problem and pollution control programmes have not been able to satisfactorily reduce this. Since traditional controls are not sufficient to reduce vehicle emissions, the application of non-intrusive Remote Sensing (RS) of vehicle emissions can make a difference. Since 2014, RS has been deployed by the Hong Kong Environmental Protection Department to identify Gasoline and Liquified Petroleum Gas fuelled vehicles excessively emitting pollutants. The assessment of the effectiveness of this RS system application by investigating the data from this programme has been undertaken. The analysis of five years of RS data from January 2012 to December 2016 showed that by 2016 that there were significant reductions of Emissions Factors ranging between 29.6% to 58.7% for HC, CO and NO. Such results highlighted that utilising RS is effectively helping to reduce vehicle emissions and improve air quality. To improve emissions failure knowledge in the automotive repair industry and in turn their capability to identify and rectify emissions problems in vehicles, a demonstration taxi with relevant engine hardware was used to simulate 15 different faults. Testing showed these faults could increase emissions by up to 317%, 782% and 282% for HC, CO and NOx respectively. The knowledge developed from this was used to educate the repair industry on the largest emissions fault sources so effective repairs could be performed. To assess RS measurement variability, calibration devices were built and tested. These identified that the temperature of exhaust gas being measured impacted the RS measurement results. To improve RS reliability, such measurements should occur 50 cm away from the exhaust tailpipe which helps reduce temperature related variability. Applying this will help to improve RS measurement accuracy, with an aim to make RS effective for all types of vehicles regardless of fuel or their size.

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http://hdl.handle.net/10453/162586