NDLI: Mass Air Flow Sensor Diagnostics for Adaptive Fueling Control of Internal Combustion Engines

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Patrick, J. Buehler Matthew, A. Franchek Makki, Imad
Copyright Year	2002
Abstract	Presented in this paper is an information synthesis (IS) approach for the mass air flow (MAF) sensor diagnosis on internal combustion engines. An information synthesis solution is attractive for diagnostics since the algorithm automatically calibrates itself, reduces the number of false detections and compresses a large amount of engine health information into the model coefficients. There are three primary parts to information synthesis diagnostics. First, an IS model is used to predict the MAF sensor output based on the engine operating condition. The inputs to this IS model include the throttle position sensor (TPS) and the engine speed sensor information. The second part concerns an online adaptation process that is used to reduce the errors between the IS model output and the actual MAF sensor output. Finally the adapted model coefficients are used to diagnose the sensor as well as identify the source for changes in the sensor characteristics. This proposed solution is experimentally tested and validated on a Ford 4.6 L V-8 fuel injected engine. The specific MAF sensor faults to be identified include sensor bias and a leak in the intake manifold.
Sponsorship	Dynamic Systems and Control Division
Starting Page	585
Ending Page	593
Page Count	9
File Format	PDF
ISBN	0791836290
DOI	10.1115/IMECE2002-32023
Volume Number	Dynamic Systems and Control
Conference Proceedings	ASME 2002 International Mechanical Engineering Congress and Exposition
Language	English
Publisher Date	2002-11-17
Publisher Place	New Orleans, Louisiana, USA
Access Restriction	Subscribed
Subject Keyword	Leakage Errors Intake manifolds Air flow Algorithms Internal combustion engines Sensors Fuels Engines
Content Type	Text
Resource Type	Article

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