Fault detection of Air Intake Systems of SI gasoline engines using mean value and within cycle models

Abstract

This paper addresses the detection of faults in Air Intake Systems (AIS) of SI gasoline engines based on realtime measurements. It presents comparison of two classes of models for fault detection, namely those using a Mean Value EngineModel (MVEM) involving variables averaged over cycles andWithin Cycle Crank-angle-based Model (WCCM) involving instantaneous values of variables changing with crank angle. Numerical simulation results of intake manifold leak and mass air flow sensor gain faults, obtained using the industry standard software called AMESimTM, have been used to demonstrate the fault detection capabilities of individual approaches. Based on these results it is clear that the method using WCCM has a higher fault detection sensitivity compared to one that uses MVEM, albeit at the expense of increased computational and modeling complexity.