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Development of misfire detection algorithm using quantitative FDI performance analysis

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.

Daniel Jung, Lars Eriksson, Erik Frisk and Mattias Krysander

Control Engineering Practice, 2015

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