DocumentCode :
3286997
Title :
Exhaust pressure estimation and its application to variable geometry turbine and wastegate diagnostics
Author :
Yue-Yun Wang ; Haskara, I.
Author_Institution :
R&D, Gen. Motors, Warren, MI, USA
fYear :
2010
fDate :
June 30 2010-July 2 2010
Firstpage :
658
Lastpage :
663
Abstract :
Exhaust pressure is a critical engine parameter used to calculate engine volumetric efficiency and EGR flow rate. In this paper, exhaust pressure is estimated for an internal combustion engine equipped with a variable geometry turbocharger. A coordinate transformation is applied to generate a turbine map for estimation of the exhaust pressure. This estimation can be used to replace an expensive pressure sensor for cost saving. On the other hand, for internal combustion engines that have already installed exhaust pressure sensors, this estimation can be used to generate residual signals for model-based diagnostics. Based on the residual signals, two diagnostic methods are proposed: one based on cumulative sum algorithms and the other based on pattern recognition and neural networks. The algorithms are able to detect and isolate different failure modes for a turbocharger system.
Keywords :
condition monitoring; exhaust systems; failure analysis; internal combustion engines; mechanical engineering computing; neural nets; pattern recognition; pressure sensors; EGR flow rate; cumulative sum algorithms; engine volumetric efficiency; exhaust pressure estimation; failure modes; internal combustion engine; model-based diagnostics; neural networks; pattern recognition; pressure sensors; variable geometry turbine; wastegate diagnostics; Atmospheric modeling; Costs; Diesel engines; Engine cylinders; Fault detection; Geometry; Internal combustion engines; Neural networks; Signal generators; Turbines; Exhaust pressure estimation; fault detection and isolation; model-based diagnostics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
ISSN :
0743-1619
Print_ISBN :
978-1-4244-7426-4
Type :
conf
DOI :
10.1109/ACC.2010.5531105
Filename :
5531105
Link To Document :
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