Diagnosis and Prognosis of Fuel Injectors based on Control Adaptation

Azeem Sarwar, Chaitanya Sankavaram, and Xiangxing Lu
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_17_049.pdf2.96 MBAugust 20, 2017 - 10:59am

Spark Ignition Direct Injection (SIDI) technology enables better fuel economy and tail pipe emissions in vehicles equipped with gasoline engines. The SIDI technology depends on the ability of the system to deliver fuel at high pressure directly into the combustion chamber, hence making the fuel injectors key subcomponents. Reliable performance of fuel injectors is vital as it directly relates to the operability of the vehicle, and hence customer satisfaction in case of failure. It, therefore, becomes very important to devise a scheme that can effectively diagnose and prognose such a component. In this article, algorithm development for diagnosis and a pathway to prognosis of fuel injectors is presented. We do not propose any additional sensing capability, and make use of what is available in most of the production vehicles today across the industry. In particular, the control adaptation of fuel control and the associated diagnostics that are mandated by regulators are employed to generate schemes for fault detection, fault isolation, and fault prediction. Results are presented from vehicle test data that allow development of such a scheme for fuel injectors.

Publication Year: 
2017
Publication Volume: 
8
Publication Control Number: 
049
Page Count: 
10
Submission Keywords: 
prognostics
Fuel system
GDI
SIDI
Submission Topic Areas: 
Component-level PHM
Data-driven methods for fault detection, diagnosis, and prognosis
Industrial applications
Model-based methods for fault detection, diagnostics, and prognosis
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