Model-based fault detection and isolation in automotive yaw moment control system View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-06

AUTHORS

Seung-Han You, Young Man Cho, Jin-Oh Hahn

ABSTRACT

This paper presents a model-based fault detection and isolation technique for automotive yaw moment control system. For this purpose, a novel fault detection and isolation algorithm for a class of actuator-plant systems is proposed. Compared with the existing fault detection and isolation techniques that can only isolate a target fault or require multiple observers to isolate multiple faults, a unique strength of the proposed algorithm is its ability to isolate faults at the component level solely based on the residuals generated by a single observer. The validity of the proposed algorithm, applied to automotive yaw moment control system, is investigated via a simulation study based on a realistic vehicle dynamics model. The results suggest that the proposed algorithm can isolate the component subject to fault while effectively handling two perennial nuisances: sensitivity to disturbances and false alarms due to uncertainties. More... »

PAGES

405-416

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12239-017-0041-5

DOI

http://dx.doi.org/10.1007/s12239-017-0041-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1084034735


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