A model-based approach is presented for the detection and isolation of faults occurring on a vehicle control system. Using multiple models and observer as virtual sensors which are based on simplified descriptions of the system, symptoms appropriate for fault diagnosis are generated. A fuzzy filter together with a knowledge base describing the relation between the faults and the symptoms are used to detect and isolate the faults as fast as possible while at the same time avoiding false alarms. The goals of the fault diagnosis are achieved by detecting faults which are classified as hazardous, achieving fast and robust fault detection, and by using simple models which enhance the feasibility of the approach for the automotive application. Using explicitly a few pressure sensors for the generation of the residuals, the cost and packaging efforts of the diagnosis system are held to a minimum. This is due to the fact that pressure sensors are commonly available in many fields of automotive applications and are easily installed relative to other types of sensors.
Fault diagnosis of an active suspension control system
Fehlerdiagnose der Regelung einer aktiven Radaufhängung
2006
6 Seiten, 10 Bilder, 11 Quellen
Conference paper
English
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