Michael James Uhrich

An evaluation of detection metrics for an integrated catalyst controller and diagnostic monitor

Abstract An integrated, model-based methodology for three-way automotive catalyst control and diagnostic monitoring utilizing a limited integrator model with an adaptive integral gain is outlined in this work. This adaptive gain, which is a measure of the catalyst oxygen storage capacity, is used both by the controller to provide information on the dynamic catalyst behavior and by the diagnostic monitor to provide information on long-term catalyst deactivation and short-term emission control device failure. Nonparametric test statistics using various metrics computed from a moving window sample of the adaptive gain are compared to determine their ability to detect changes in catalyst system performance with a number of differently aged catalysts. These diagnostic monitoring metrics have been applied to 4.6 liter ULEV II gasoline engine data tested over an EPA Federal Test Procedure drive cycle.

A probability density metric for automotive three-way catalyst diagnostics

A statistical classification technique based on the fraction of time the catalyst gain is very close to zero is used as a diagnostic metric for on-board monitoring of an automotive catalyst. Preliminary results indicate that it is possible to perform very accurate discrimination between catalyst operation, even near the on-board diagnostic detection threshold, using this technique. Experimental vehicle tests with each of the different catalysts are used as the basis for comparison.

Probability density diagnostic metric for an integrated three-way catalyst controller and monitor

Abstract An integrated model-based methodology for three-way automotive catalyst control and diagnostic monitoring is presented in this work. The catalyst controller and monitor both utilize a limited integrator catalyst oxygen storage model with an adaptive integral gain. This adaptive catalyst gain, which is a measure of the catalyst oxygen storage capacity, is used by the controller to provide information on the dynamic catalyst behaviour and by the diagnostic monitor to provide information on long-term catalyst deactivation and short-term emission control device failure. A statistical classification technique based on the fraction of time that the catalyst gain values in a moving window are within a threshold of zero is employed as the test metric for on-board diagnostic monitoring. The performance of the catalyst monitor is demonstrated with experimental vehicle test data from a 4.6 l ULEV II gasoline engine operated over a series of Environmental Protection Agency Federal Test Procedure drive cycles with differently aged catalysts. Preliminary results indicate that it is possible to perform very accurate discrimination between catalyst operation, even near the on-board diagnostic detection threshold, using this technique.