TY - JOUR
T1 - Fault detection isolation and estimation in a vehicle steering system
AU - Arogeti, Shai A.
AU - Wang, Danwei
AU - Low, Chang Boon
AU - Yu, Ming
N1 - Funding Information: Manuscript received November 13, 2010; revised July 10, 2011 and October 15, 2011; accepted November 16, 2011. Date of publication January 11, 2012; date of current version July 2, 2012. This work was supported in part by the A∗Star SERC under Grant 0521160078.
PY - 2012/7/17
Y1 - 2012/7/17
N2 - 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.
AB - 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.
KW - Fault detection and isolation
KW - fault estimation
KW - global analytical redundancy relations
KW - hybrid bond graph
UR - http://www.scopus.com/inward/record.url?scp=84863739528&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/TIE.2012.2183835
DO - https://doi.org/10.1109/TIE.2012.2183835
M3 - Article
SN - 0278-0046
VL - 59
SP - 4810
EP - 4820
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 12
M1 - 6129421
ER -
