Abstract
A model-based three-way automotive catalyst monitoring and fault detection strategy is presented in this work. A simplified oxygen storage and reversible catalyst deactivation model is employed to predict the measured postcatalyst air fuel ratio. A fault is assumed to be present in the system when the current distribution of the post-catalyst air fuel ratio prediction error differs from the base operating distribution. Changes in the post-catalyst air fuel ratio prediction error distribution are indicative of both long-term catalyst poisoning effects and short-term emission control device failures. These changes are detected based on the results of a Kolmogorov-Smirnov test Using sampled cumulative distribution functions. A moving horizon approach is used to determine the current error distribution.
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