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Gas-sensors for Automobile Interiors
Linköping University, Department of Physics, Measurement Technology, Biology and Chemistry. Linköping University, The Institute of Technology.
2000 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The concentration of pollutants in the car compartment air is influenced not only by neighboring vehicles, but also by pollutants originating from the car's interior trim materials. These pollutants may cause nuisance and even pose a safety risk as some condense on the windscreen and form an oily film that dims the screen.

This thesis is primarily the outcome of a joint-effort of Volvo Material Laboratory and Applied Physics, University of Linköping. The aim of this project was to gain information about the usefulness of an electronic nose in improving the car indoor environment.

The intention of this thesis is to give an idea of the state of the art of the two disciplines: gas-sensor science and indoor air quality studies, and in particular in relation to car indoor air.

The work involves comparison of the responses of a so called electronic nose to traditional analytical chemistry methods involving gas chromatography/mass spectrometry (GC/MS) and high performance liquid chromatography (HPLC) as well as comparison to the odor intensity assessed by human sensory panels. An electronic nose is a combination of a chemical sensor array and pattern recognition software. The electronic nose used consisted of gas-sensors based on semiconducting metal oxides (MOSs) and metal-oxide-semiconductor field-effect transistors (MOSFETs).

The instrument has been tested both in driving situations and under static conditions. Its usefulness in material development and off-line quality monitoring is shown.

The thesis also contains the first report on chemical gas sensing of solid material, by the combination of gas sensors and pyrolysis.

In addition new knowledge on how to improve sensor stability is presented.

Different sensor techniques as well as different pattern recognition techniques are treated and commercially available instruments listed.

In this work the great potential of the technique is shown and directions for furtherstudies are indicated.

Place, publisher, year, edition, pages
Linköping: Linköping University , 2000. , p. 46
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 655
National Category
Materials Chemistry
Identifiers
URN: urn:nbn:se:liu:diva-186983Libris ID: 7624639ISBN: 9172198478 (print)OAI: oai:DiVA.org:liu-186983DiVA, id: diva2:1682302
Public defence
2000-10-18, Planck, Fysikhuset, Linköpings universitet, Linköping, 13:00
Opponent
Note

All or some of the partial works included in the dissertation are not registered in DIVA and therefore not linked in this post.

Available from: 2022-07-08 Created: 2022-07-08 Last updated: 2022-07-08Bibliographically approved
List of papers
1. Classification of complex gas mixtures from automotive leather using an electronic nose
Open this publication in new window or tab >>Classification of complex gas mixtures from automotive leather using an electronic nose
2000 (English)In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 403, no 1-2, p. 31-38Article in journal (Refereed) Published
Abstract [en]

A semiconductor gas sensor array combined with a routine for pattern recognition - a so-called electronic nose - for the detection of gas emissions from the leather used in car compartments is described. The gas sensors are 10 metal oxide semiconductor field effect transistors (MOSFETs) with gates of thin, catalytic metals, and five semiconducting metal oxide sensors. The sensor array data are processed by multivariate means using principal component analysis (PCA) and are shown to give similar and add additional information compared to gas chromatography-mass spectrometry (GC- MS) and a human sensory panel. The total volatile organic compound concentration as measured by GC did not differ between good and bad samples and could therefore not be used as a quality control tool, whilst the electronic nose together with pattern recognition could readily discover the deviating samples with unusual emitting gases. This set-up could be useful in on-line quality monitoring systems to detect anomalies in incoming car interior trim materials.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-47709 (URN)10.1016/S0003-2670(99)00604-2 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2022-07-08
2. Chemical gas sensors for car exhaust and cabin air monitoring
Open this publication in new window or tab >>Chemical gas sensors for car exhaust and cabin air monitoring
Show others...
2002 (English)In: Indoor + Built Environment, ISSN 1420-326X, E-ISSN 1423-0070, Vol. 11, no 2, p. 105-110Article in journal (Refereed) Published
Abstract [en]

A combination of charcoal and particle filters has previously been shown to reduce effectively the smell of diesel exhaust. In this paper it is shown that the smell of diesel exhaust can successfully be predicted by the concentration of total volatile organic compounds and the concentration of certain carbonyl compounds. Projection to latent structures was utilised for model building. An electronic nose consisting of MOSFET and MOS sensors could less successfully predict the smell, but identified the same filter combination as being most efficient. The car cabin air during urban driving was also monitored, both by the means of MOSFET sensors and by chemiluminescence. The pollution level inside the car is shown to be elevated by about 30% compared to outside the car. A combination filter together with an air inlet sensor switch is shown to reduce the NOx levels inside the car by 30% compared to outside, with the ability to significantly decrease the peak levels. Copyright © 2002 S. Karger AG, Basel.

Keywords
Air inlet filter, Cabin air, Diesel exhaust, Electronic nose
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-46943 (URN)10.1159/000064246 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2022-07-08

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