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Automotive Diagnostic Decisions Using Probabilistic Information

[+] Author Affiliations
Matthew L. Schwall, J. Christian Gerdes

Stanford University

Paper No. IMECE2005-82169, pp. 157-166; 10 pages
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Engineering/Technology Management
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Engineering and Technology Management Group
  • ISBN: 0-7918-4230-4 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME


Safety, emissions, and driver demands all require progressively better automotive fault detection, identification, and recovery (FDIR). Probabilistic diagnostics represents an effective way of improving fault detection and identification even as vehicle complexity increases. This paper presents a method for making decisions based on fault probabilities, so that these advances can enable more effective fault recovery. The decision maker’s goal is to choose a set of actions that minimizes risks resulting from faults, and this requires analyzing the temporal behavior of the faults and actions. Using a vehicle’s stability control system as an example, a method is presented for modeling these dynamics and determining the optimal decision strategy. Most calculations can be performed off line and stored, enabling efficient real-time decision making. The paper concludes by presenting the optimal decision strategy for the vehicle example.

Copyright © 2005 by ASME



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