Adaptive Model Predictive Control of an SCR Catalytic Converter System for Automotive Applications


Selective catalytic reduction (SCR) is returning into worldwide use for diesel engine emissions reduction of on- and off-highway vehicles. These applications are characterized by broad operating vary in addition to rapid and unpredictable changes in operating condition. Vital nonlinearity, input, and output constraints, and stringent performance necessities have led to the proposal of many completely different advanced control ways. This article introduces a model predictive feedback controller based mostly on a nonlinear, reduced order model. Computational effort is significantly reduced through successive linearization, analytical solutions, and a varying terminal value perform. A gradient-based parameter adaptation law is utilized to attain consistent performance. The controller is demonstrated in simulation for an on-highway serious-duty diesel engine over 2 widely completely different emissions test cycles and for twenty-four completely different plants. Comparisons with baseline management designs reveal the attractive features with the limitations of this approach.

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