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

Title data

Walter, Stefanie ; Schwanzer, Peter ; Hagen, Gunter ; Rabl, Hans-Peter ; Dietrich, Markus ; Moos, Ralf:
Soot Monitoring of Gasoline Particulate Filters Using a Radio-Frequency-Based Sensor.
In: Sensors. Vol. 23 (2023) Issue 18 . - 7861.
ISSN 1424-8220

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Load Sensor for GPF

Project financing: Bayerische Forschungsstiftung

Abstract in another language

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.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Functional Materials > Chair Functional Materials - Univ.-Prof. Dr.-Ing. Ralf Moos
Profile Fields > Advanced Fields > Advanced Materials
Research Institutions > Central research institutes > Bayreuth Center for Material Science and Engineering - BayMAT
Research Institutions > Research Units > BERC - Bayreuth Engine Research Center
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 18 Sep 2023 10:32
Last Modified: 18 Sep 2023 10:32