Uncertainties in emissions measurements in a partial flow sampling system

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3 Scopus citations

Abstract

This paper investigates experimental uncertainties associated with gaseous and particulate emissions measurements in a partial flow emissions sampling system developed and built at the Larson Transportation Institute of the Pennsylvania State University. A small fraction of the tail pipe exhaust is diluted with dilution air and passed through a cyclone to eliminate particles bigger than 2.5 microns. The diluted exhaust is then passed through a 47 mm Teflon filter for gravimetric measurement of Particulate Matter (PM). Mass flow controllers operating at 5Hz are used to control the flow rates of dilution air, diluted exhaust, and proportional flow of diluted exhaust into a Tedlar bag. An ultrasonic flow meter is used to measure flow rate of tail pipe exhaust. At the end of a test, the concentration of gaseous emissions in the bag, namely CO2, CO, HC, and NOx are measured using a bag emissions analyzer. The mass of gaseous and PM emissions in the tail pipe exhaust for the duration of a test are calculated using the measured gas concentrations in the bag and weight gain of the filter respectively. An uncertainty analysis on the results from an actual test using this system is presented. The propagation of uncertainties in the subsystems used for gas concentration measurements, filter weight determination, and flow rate measurements are used to determine the uncertainties in the results, using the Root Sum Square (RSS) method. The measurement uncertainties from this partial sampling system are then compared to the measurement uncertainties from a full flow dilution tunnel equipped with emissions analyzers for the same test, when both systems are drawing samples simultaneously.

Original languageEnglish (US)
DOIs
StatePublished - Jan 14 2015
Event14th Symposium on International Automotive Technology, SIAT 2015 - Pune, India
Duration: Jan 21 2015Jan 23 2015

Other

Other14th Symposium on International Automotive Technology, SIAT 2015
CountryIndia
CityPune
Period1/21/151/23/15

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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