Model Predictive Functional Control for an Automotive Three-way Catalyst

Document Number: 2009-01-0728

Date Published: April 2009

Author(s):
Robert Schallock - Villanova University
Kenneth Muske - Villanova University
James C. Peyton Jones - Villanova University

Abstract:
In this work, a model predictive functional control approach for automotive three-way catalyst oxygen storage state control is demonstrated on a Ford 2.0-liter I4 Duratec SI engine. The control system uses a UEGO sensor for the pre-catalyst air-fuel ratio (AFR) measurement and a switching-type HEGO sensor for the post-catalyst measurement. The model predictive controller is the primary control loop within a multi-rate cascade control configuration that adapts the parameters of a post-catalyst HEGO relay controller in an optimal manner using a predictive functional control approach. This relay controller adjusts the target of a delay-compensated feedback controller for the pre-catalyst AFR in order to maintain the post-catalyst HEGO sensor signal within a specified range of the desired target voltage. The use of a multi-rate cascade control structure allows the relay controller to execute within a short control interval in order to ensure that the post-catalyst HEGO sensor does not saturate and allows the model predictive controller to execute within a longer control interval in order to provide sufficient computation time to perform the on-line optimization necessary for predictive control. This cascade structure can also tolerate failure of the catalyst controller to solve the online optimization problem because the post-catalyst relay controller will continue to stabilize the catalyst system without the predictive controller operating.

File Size: 575K
Product Status: In Stock

Included in: V118-4

See other papers presented at SAE World Congress & Exhibition, April 2009, Detroit, MI, USA, Session: Electronic Engine Controls (Part 3 of 5)

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