Search Results

Increasingly tighter automotive emissions legislation not only demands advanced catalyst control for super ultra low emission vehicle (SULEV) requirements, but also a close monitoring of catalyst performance. In the present paper, a control-oriented model is proposed that uses a library of four nonlinear (NARMAX) dynamic models to predict the three-way catalyst (TWC) transient response. Each nonlinear model is optimised for use under a certain operating region. In order to identify the current operating region and select the appropriate local model for prediction, the rate of change of stored oxygen is monitored. A simplified chemical model, which is based on the dynamics of the fundamental chemical reactions that occur inside the catalyst, is used for this purpose. The developed catalyst model only requires knowledge of the upstream/downstream air-fuel ratio (AFR) and it could form the basis of an on-board catalyst monitoring and control system.

Transient measurements of pre- and post-catalyst exhaust gas components and AFR are used to investigate the relationship between post-catalyst AFR and tailpipe emissions. This relationship is critical to the ability of on-board oxygen storage dominated models to predict emissions levels. The results suggest that under rich, or rich-biased conditions, dynamic deactivation processes significantly reduce catalyst efficiency, and that modeling oxygen storage effects alone may result in over-prediction of tailpipe pollutants. Catalyst deactivation is also shown to be correlated to hydrogen-induced distortion in the Exhaust Gas Oxygen (EGO) sensors used for measuring AFR. The dynamics of reversible catalyst deactivation are therefore important both for its direct effect on dynamic conversion efficiency, and for its indirect effect on dual EGO sensor dependent catalyst control and OBD strategies

The relationship between the concentration of various gas components (CO,NO,HC) at the output of a three-way catalytic converter and the input and output air-fuel ratios (AFRs) is examined. A simple linear-in-the-parameters model is developed and it is assumed that the model parameters in the lean and rich regions are different. The model is fitted to some experimental step response data obtained from fast gas response analysers and UEGO sensors, using a recursive linear least-squares estimation method. A reasonably good fit to the data is obtained, particularly for NO and CO. Results from step tests for different AFR ranges are combined to obtain an overall picture of the dependency of the gas components on measured AFR values. The proposed model provides the possibility of predicting the dynamic performance of catalytic converters from a knowledge of the input and output AFR values.

The transient response of a catalytic converter to fluctuations in exhaust gas composition has a significant impact on tailpipe emissions. Advanced emission control strategies therefore need to incorporate a model for such behavior, which must also be sufficiently simple for practical implementation in-vehicle. To this end, a variety of semi-empirical models have been developed, including most recently a number of oxygen “storage-dominated” models. In this paper a new storage-dominated model is developed, which includes for the first time the effects of space velocity. The parameters of model may be estimated using the invariant embedding method.

The gas components CO, CO2, HC, NOx and the AFR in the exhaust from a SI engine, both upstream and down-stream of a Pd/Rh catalytic converter, have been monitored using fast response analyzers. Regular sequential step changes in the upstream air/fuel ratio (AFR), between two pre-set levels, have been implemented with both long and short periods between the steps. For transitions from rich to lean conditions, and vice-versa, several distinct zones for the output emissions characteristics, corresponding to different states of the catalyst surface, have been identified. These results suggest that, under reducing conditions, hydrogen is stored on the catalyst surface whereas under oxidizing conditions oxygen is stored by two different processes. These chemical insights facilitate the development of realistic models for tailpipe emissions from engines which are perturbed from steady state running.

The dynamic behavior of three-way catalysts has significant impact on tailpipe emissions levels, but remains one of the last unknowns in the overall vehicle emissions model. A simple empirical model (appropriate for use in real-time engine control and on-board diagnostic strategies) has therefore been identified using fast response input / output measurements of the actual process. The model is able to characterize the (significant) dynamic behavior which has recently been observed under rich conditions, as well as the more well known dynamics which arise from oxygen storage. The results therefore compare well with measured responses over a wide range of air / fuel ratio conditions.