Diagnosis of failures in a spark ignition engine using fuzzy logic

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Author: 
Néstor Rivera, Jairo Castillo, Steven Ronquillo, Yasmani Aguilar
Abstract: 

This document presents the development of a system for detecting faults through fuzzy logic, using different parameters such as poorly combusted hydrocarbons (HC), Carbon Dioxide (CO2), engine speed (RPM), and Manifold Absolute Pressure Sensor (MAP) to predict the faults that may occur in the engine. In order to determine the behavior of the inputs, there were generated different faults in a sonata 2.0 gasoline engine, such as poorly calibrated spark plugs, improper fuel pressure, air filter and catalytic converter clogging. The input and output variables are analyzed by fuzzy logic. Rules are generated for these variables, which will give logical knowledge to the system; these proposed rules are verified through the system programming that is presented by simulink. Each input variable establishes a diverse output parameter. Through this system, it can be determined the level of the response parameters, which will give reliable values for detecting the faults when performing corrective maintenance; consequently, it will save time and money.

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