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Soot Monitoring of Gasoline Particulate Filters Using a Radio-Frequency-Based Sensor

  • Owing to increasingly stringent emission limits, particulate filters have become mandatory for gasoline-engine vehicles. Monitoring their soot loading is necessary for error-free operation. The state-of-the-art differential pressure sensors suffer from inaccuracies due to small amounts of stored soot combined with exhaust gas conditions that lead to partial regeneration. As an alternative approach, radio-frequency-based (RF) sensors can accurately measure the soot loading, even under these conditions, by detecting soot through its dielectric properties. However, they face a different challenge as their sensitivity may depend on the engine operation conditions during soot formation. In this article, this influence is evaluated in more detail. Various soot samples were generated on an engine test bench. Their dielectric properties were measured using the microwave cavity perturbation (MCP) method and compared with the corresponding sensitivity of the RF sensor determined on a lab test bench. Both showed similar behavior. The values for the soot samples themselves, however, differed significantly from each other. A way to correct for this cross-sensitivity was found in the influence of exhaust gas humidity on the RF sensor, which can be correlated with the engine load. By evaluating this influence during significant humidity changes, such as fuel cuts, it could be used to correct the influence of the engineon the RF sensor.

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Metadaten
Author:Stefanie WalterORCiD, Peter SchwanzerORCiD, Gunter Hagen, Hans-Peter Rabl, Markus Dietrich, Ralf Moos
DOI:https://doi.org/10.3390/s23187861
ISSN:1424-8220
Parent Title (English):Sensors
Publisher:MDPI
Document Type:Article
Language:English
Year of first Publication:2023
Release Date:2023/10/17
Tag:dielectric properties; engine test bench; gasoline particulate filter (GPF); microwave cavity perturbation; radio-frequency (RF); soot mass determination
Volume:23
Issue:18
Article Number:7861
First Page:1
Last Page:19
Note:
This research work was funded by the Bavarian Research Foundation (Bayerische Forschungsstiftung, BFS) as part of the project “Load Sensor for GPF” (AZ-1288-17).
Institutes:Fakultät Maschinenbau
Begutachtungsstatus:peer-reviewed
OpenAccess Publikationsweg:Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium
research focus:Energie und Mobilität
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International