Date of Award
8-1-2018
Degree Name
Master of Science
Department
Electrical and Computer Engineering
First Advisor
Kagaris, Dimitrios
Abstract
Current OBD-II vehicle systems detect misfires by monitoring slight variances of crankshaft acceleration throughout power-strokes of each of the engine’s cylinders. If the PCM determines that the acceleration of the engine’s crankshaft is inappropriate, it concludes a misfire is detected. However, after this misfire is detected, the technician still needs to diagnose (isolate) the root-cause. Diagnosis is no easy task, especially with several potential subsystems that could be at fault: fuel injection, air-intake, sparkignition, and engine-mechanical. With this being said, it is difficult for many technicians to isolate the fault causing a misfire because of the wide range of root-cause possibilities within each of the subsystems. The proposed On-Board Diagnostics III contributes to the computer-aided detection and diagnosis of future-production vehicle faults. Several data-mining algorithms were investigated and applied to data parameters collected from misfire and misfire-free fault instances. Rules were then used to accurately classify future engine misfire fault instances.
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