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• W3149833928 abstract "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 thefuel 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." @default.
• W3149833928 created "2021-04-13" @default.
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• W3149833928 date "2017-01-01" @default.
• W3149833928 modified "2023-09-23" @default.
• W3149833928 title "Diagnosis and Prognosis of Fuel Injectors based on Control Adaptation" @default.
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• W3149833928 doi "https://doi.org/10.36001/phmconf.2017.v9i1.2469" @default.
• W3149833928 hasPublicationYear "2017" @default.
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