4.6 Article

Development of misfire detection algorithm using quantitative FDI performance analysis

Journal

CONTROL ENGINEERING PRACTICE
Volume 34, Issue -, Pages 49-60

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.conengprac.2014.10.001

Keywords

Misfire detection; Fault diagnosis; Fault detection and isolation; Kullback-Leibler divergence; Pattern recognition

Funding

  1. Volvo Car Corporation
  2. Swedish Research Council within the Linnaeus Center CADICS

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A model-based misfire detection algorithm is proposed. The algorithm is able to detect misfires and identify the failing cylinder during different conditions, such as cylinder-to-cylinder variations, cold starts, and different engine behavior in different operating points. Also, a method is proposed for automatic tuning of the algorithm based on training data. The misfire detection algorithm is evaluated using data from several vehicles on the road and the results show that a low misclassification rate is achieved even during difficult conditions. (C) 2014 Elsevier Ltd. All rights reserved.

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