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Fault Diagnostics (ME8372)

Course Description

System fault diagnosis is of growing importance in the automotive industry and in many other fields due to the desire to guarantee system availability and satisfy regulations related to safety and environmental impact.
This course covers the theory and application of fault diagnosis in multi-domain dynamic systems. The course culminates in the completion of a project in which students design and implement a diagnostic system in simulation.
Linear system theory or a control course based on state-space concepts is required. Knowledge of concepts such as system stability, controllability and observability is essential and proficiency in Matlab is also required. CAR preparatory seminars in Linear Systems and Matlab are recommended. 

Goals

Upon completion of this course participants will be able to:

  • Understand ISO standard 26262 in functional safety used in automotive industry
  • Demonstrate a systems approach for the development of diagnostic algorithms based on dynamic system models (analytic redundancy) and on the analysis of sensor signals
  • Perform analysis with fault trees, failure mode and effects analysis (FMEA), hazard and fault analysis
  • Design procedures for diagnostic observers and estimators and diagnostic applications of signal processing with special emphasis on application and implementation issues

Faculty

Giorgio RizzoniGiorgio Rizzoni has served in his current role as director for the Center for Automotive Research since 1999, while holding faculty appointments in both Mechanical and Aerospace Engineering (MAE) and Electrical and Computer Engineering (ECE). He has been continuously engaged in graduate and undergraduate curriculum development on subjects related to system dynamics, mechatronics, powertrain modeling, hybrid-electric vehicles and system fault diagnosis. Rizzoni is a three-time recipient of the MAE External Advisory Board Excellence in Teaching Award and in 1996 received the College of Engineering Stanley Harrison Award for Excellence in Engineering Education.