A fuzzy model for an automotive engines-development on a production vehicle

Abstract EN

In this paper, we developed a fuzzy model for an automotive engine.

The fuzzy model was presented by a set of rules based on the Takagi-Sugeno type.

The Gustafson-Kessel (GK) algorithm was applied to determine the antecedent membership functions and eastsquare estimation was used to determine the consequence parameters.

The performance of the fuzzy model was tested using a set of measurements recorded from a single production vehicle with a 3.1 I V-6 engine and a four speed automatic transmission.

This data was collected earlier during a project implemented at George Mason University, USA.

The developed fuzzy model was able to provide a good modeling capabilities.