Model-Based Estimation and Control System Development in a Urea-SCR Aftertreatment System

TL;DR: A model-based linear estimator and a nonlinear control law for an Fe-zeolite ureaselective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented, which uses less urea, produces less NH3 slip, and less tailpipe NOx than a similar strategy.

Abstract: In this paper, a model-based linear estimator and a nonlinear control law for an Fe-zeolite ureaselective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design. An experimentally validated, higher order simulation is used to evaluate the performance of the closed loop system. For the cases considered, the control strategy uses less urea, produces less NH3 slip, and less tailpipe NOx than a similar strategy where NO and NO2 are assumed as all NO during estimation and control law implementation.