Fault detection isolation and estimation in a vehicle steering system

Shai A. Arogeti, Danwei Wang, Chang Boon Low, Ming Yu

Research output: Contribution to journalArticlepeer-review

82 Scopus citations

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.

Original languageEnglish
Article number6129421
Pages (from-to)4810-4820
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume59
Issue number12
DOIs
StatePublished - 17 Jul 2012

Keywords

  • Fault detection and isolation
  • fault estimation
  • global analytical redundancy relations
  • hybrid bond graph

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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