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Technical Paper

Fast Response NDIR for Real-Time Exhaust Measurement

1990-02-01
900501
The objective of the work was to develop a fast response infrared analyzer that makes possible the cyclic measurement of exhaust gas concentrations from internal combustion engines. The new analyzer achieves T90 response time of less than 30 milliseconds and is capable of measuring CO, CO2 and HC (Hydrocarbons) simultaneously. Another feature of the analyzer is its' capability to measure simultaneously from multiple sample points, i.e., one optical bench with a maximum of four sample cells can measure CO, CO2 and HC simultaneously from four different sources. Results from a multiple cylinder engine show that this analyzer can be an effective tool for analysis and diagnosis of internal combustion engine exhaust products.
Technical Paper

Performance Test Results of a New On Board Emission Measurement System Conformed with CFR Part 1065

2007-04-16
2007-01-1326
A new on-board portable emission measurement system (PEMS) for gaseous emissions has been designed and developed to meet CFR Part 1065 requirements. The new system consists of a heated flame ionization detector (HFID) for the measurement of total hydrocarbon, a heated chemiluminescence detector (HCLD) for the measurement of NOx, and a heated non-dispersive infra-red detector (HNDIR) for the measurement of CO and CO2. The oxygen interference and relative sensitivity of several hydrocarbon components have been optimized for the HFID. The CO2 and H2O quenching effect on the HCLD have been compensated using measured CO2 and H2O concentration. The spectral overlap and molecular interaction of H2O on the HNDIR measurement has also been compensated using an independent H2O concentration measurement. The basic performance of the new on-board emission measurement system has been verified accordingly with CFR part 1065 and all of the performances have met with CFR part 1065 requirement.
Technical Paper

Hydrocarbons Speciation of Automotive Emissions Using High Speed Gas Chromatography

1995-02-01
950513
A high speed gas chromatography system has been developed for automotive emissions measurement. The system is capable of quantifying hydrocarbons from C2 to C12 compounds. The separation time required for an analysis is only five minutes. Major technical challenges were (1) tandem quick heat cold traps, (2) four parallel ovens design, and (3) the mid-point back flush technique. Demonstrations of the system have been done using FTP75 cold transient phase. The results indicate that the system is well suited for hydrocarbon speciation measurement with very simple and quick operations.
Technical Paper

Exhaust Gas Analysis for Automobile Quality Control by a New Non-Dispersive Infrared Gas Analyzer

1982-02-01
820055
This report describes a new, maintenance-free exhaust gas analysis system for automobile quality control. It incorporates non-dispersive infrared. (NDIR) gas analyzers employing a cross-flow modulation method which provides virtually drift-free performance and eliminates the need for optical adjustment, Analyzer modulation is by means of alternating the flow of sample gas and reference gas into two cells with a rotary valve of simple construction. Microcomputers are used for system control and to process the data. This system measures oxides of nitrogen (NOx), total hydrocarbon (THC) and carbon monoxide/dioxide (CO/CO2) with three analyzers. Full scale ranges of 50 ppm for NOx and 20 ppm for THC are feasible with cells merely 35 mm long. In each case the signal-to-noise ratio is 100. In actual operation, the system drift was so low that it required no span calibration over a period of three months.
Journal Article

THC Concentration Estimation Model using FTIR Spectrum

2021-09-21
2021-01-1226
A novel total hydrocarbon (THC) emission concentration estimation model is proposed for reduction of engine development cost and simplification of exhaust measurements. The proposed method uses the absorbance spectra of a Fourier transform infrared (FTIR) spectrometer, which contains the information on a wide variety of hydrocarbons, as input. The model is based on machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) regression and bagging techniques. To train the model, we created a dataset containing pairs of a spectrum of engine exhaust gas and the THC concentration. In addition, we incorporate absorbance spectra of individual hydrocarbon components and several inorganic components so that the model learns the contribution of each hydrocarbon to THC concentration and to ignore interferences of irrelevant gas components.
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