Modeling of three-way catalyst behavior in stoichiometric engines is a tovpic with significant depth of research which encompasses complex kinetics based models through highly simplified control-oriented models. For model based control design, one must consider the behavior of the catalyst in conjunction with the feedback oxygen sensors. These sensors have well known influences from exhaust gas species due to interaction with the catalyst which, if ignored, can cause significant difficulties in modeling and control. These effects have often been addressed by calibrating and validating catalyst models under simplified conditions in order to minimize errors. In this work, the root cause of many of these errors is investigated and experimental evidence presented. Additionally, ARMA and Hammerstein models are used to find a model capable of predicting the post-catalyst oxygen sensor response over realistic validation data.

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