Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/95839
Title: Fault detection isolation and estimation in a vehicle steering system
Authors: Yu, Ming
Arogeti, Shai A.
Wang, Danwei
Low, Chang Boon
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Arogeti, S. A., Wang, D., Low, C. B., & Yu, M. (2012). Fault Detection Isolation and Estimation in a Vehicle Steering System. IEEE Transactions on Industrial Electronics, 59(12), 4810-4820.
Series/Report no.: IEEE transactions on industrial electronics
Abstract: Recently, a bond-graph-based fault detection and isolation (FDI) framework has been developed with a new concept of global analytical redundancy relations (GARRs) (Low, Wang, Arogeti, and Luo, 2009, 2010; Low, Wang, Arogeti, and Zhang, 2010). This new concept allows the fault diagnosis for hybrid systems which consist of both continuous dynamics and discrete modes. A failure of a safety critical system such as the steering system of an automated guided vehicle may cause severe damage. Such failure can be avoided by an early detection and estimation of faults. In this paper, the newly developed FDI method is studied in details using an electrohydraulic steering system of an electric vehicle. The steering system and faults are modeled as a hybrid dynamic system by the hybrid bond graph (HBG) modeling technique. GARRs are then derived systematically from the HBG model with a specific causality assignment. Fault detection, isolation, and estimation are applied, experimental setup is described, and results are discussed.
URI: https://hdl.handle.net/10356/95839
http://hdl.handle.net/10220/11413
DOI: 10.1109/TIE.2012.2183835
Rights: © 2012 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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