• DocumentCode
    1097592
  • Title

    Detection of sensor failures in automotive engines

  • Author

    Rizzoni, Giorgio ; Min, Paul S.

  • Author_Institution
    Dept. of Mech. Eng., Ohio State Univ., Columbus, OH, USA
  • Volume
    40
  • Issue
    2
  • fYear
    1991
  • fDate
    5/1/1991 12:00:00 AM
  • Firstpage
    487
  • Lastpage
    500
  • Abstract
    The real-time application of detection filters to the diagnosis of sensor failures in automotive engine control systems is presented. The detection filter is the embodiment of a model-based failure detection and isolation (FDI) methodology, which utilizes analytical redundancy within a dynamical system to isolate the cause and location of abnormal behavior. The philosophy and essential features of FDI theory are presented, and the practical application of the method to the diagnosis of faults in some key sensors in an electronically controlled internal combustion engine is described. The experimental results presented here have been obtained on a production vehicle, and demonstrate that the real-time implementation of such detection filters is feasible, opening the way to a new generation of diagnostic strategies
  • Keywords
    automatic test equipment; automotive electronics; electric sensing devices; failure analysis; fault location; filtering and prediction theory; internal combustion engines; FDI theory; analytical redundancy; automotive engine control systems; automotive test equipment; detection filters; electrical faults; electronically controlled engine; failure isolation; internal combustion engine; model-based failure detection; production vehicle; real-time implementation; sensor failures; Automotive engineering; Control systems; Failure analysis; Fault detection; Fault diagnosis; Filters; Internal combustion engines; Real time systems; Redundancy; Sensor systems and applications;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/25.289431
  • Filename
    289431