Date of Award
10-5-2017
Publication Type
Master Thesis
Degree Name
M.A.Sc.
Department
Mechanical, Automotive, and Materials Engineering
Keywords
Direct Injection, GPF, Radio Frequency, Soot
Supervisor
Sobiesiak, Andrzej
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
Gasoline Direct Injection (GDI) engines represent a promising technology for facing the more and more stringent limits imposed by emission regulations. However, one of the drawbacks of GDI engines compared to PFI engines is the production of soot. One of the possible solutions to reduce the amount of soot emitted in the atmosphere, among the different existent strategies, is the Gasoline Particulate Filter (GPF). Nowadays, the most common device in cars for monitoring the filter state and trigger the regeneration event is the differential pressure sensor. However, this provides an indirect measure of the soot state of the filter using a predictive model implemented in the Electronic Control Unit (ECU). A valid alternative, in laboratory environment, is represented by the Radio Frequency sensor. The objective of the study is to determine if a correlation exists between the output of the RF sensor and the amount of soot in the filter. The final outcome will be an analytical model that uses the average forward gain recorded from the Radio Frequency sensor and the exhaust gas temperature that can be used to estimate the amount of soot on the filter during both loading and regeneration phases. Moreover, with the output of the model during the regeneration event, it will be possible to understand when the soot oxidation starts and to distinguish the different soot reactivity, i.e. how it differently oxidizes during regeneration.
Recommended Citation
Fiano, Angela, "A model for soot load estimation in a Gasoline Particulate Filter using a Radio Frequency sensor" (2017). Electronic Theses and Dissertations. 7257.
https://scholar.uwindsor.ca/etd/7257