Real Time Detection Filters for Onboard Diagnosis of Incipient Failures

This paper presents the real time implementation of detection filters for the diagnosis of incipient failures in electronically controlled internal combustion (IC) engines. The detection filters are implemented in a production vehicle.

Recent results [1] have demonstrated the feasibility of a model-based failure detection and isolation (FDI) methodology for detecting partially failed components in electronically controlled vehicle subsystems. The present paper describes the real time application of the FDI concept to the detection of faults in sensors associated with the engine/controller

In a detection filter, the performance of the engine/controller system is continuously compared to a prediction based on sensor measurements and an analytical model (typically a control model) of the system. Any discrepancy between actual and predicted performance is analyzed to identify the unique failure signatures related to specific system components.

The FDI methodology described in this paper is applicable to any electronically controlled subsystem; the real time implementation suggests its potential for increasing overall system reliability.