Application of Extended Kalman Filter to Fault Diagnosis System of a Gasoline Engine

The evaluation of the diagnostic equipment for automotive application is the direct effect of the implementation of sophisticated and high technology control systems in the new generation of passenger cars. In this paper three different air path faulys of a gasoline engine have been taken under consideration: inlet manifold pressure sensor fault, air mass flow sensor fault and leakage in the inlet manifold. An extended Kalman filter (EKF) is used as an observer of the system in order to estimate the different fault parameters. Only one fault parameter is mentioned at a time. Simulation with high inlet manifold pressure has values. For simulations with low pressure in the inlet manifold the results are less good, probably due to the model errors. The EKF has proved to perform well in this type of application, as an observer for a diagnosis system of an automotive engine.

Keywords:

Identification , Extended Kalman Filter , Engine Modeling , Fault Diagnosis