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