NOx sensor-based state estimations for urea-based selective catalytic reduction (SCR) systems have attracted much attention in the past several years because of their significant importance in achieving high NOx conversion efficiency and low ammonia slip at low operation cost. Most of the existing SCR state estimation techniques require sophisticated design processes and significant tuning efforts, which may prevent them from widespread applications to production urea-SCR systems. In addition, the existing SCR state observers may not be able to achieve fast and accurate estimations due to the corresponding slow estimation error dynamics. The purpose of this study was to design a straightforward and effective NOx sensor-based SCR state estimation algorithm for decoupling post-SCR NOx sensor signals (NOx concentration, ammonia concentration), and for estimating ammonia coverage ratio of the urea-SCR systems. A singular-perturbation-based approach was applied to attain the reduced-order SCR model by decoupling the fast NO and NH3 concentration dynamic models from the slow ammonia coverage ratio dynamics model. Based on the reduced-order model, a direct algebraic approach (DAA)-Newton observer was proposed for estimating ammonia coverage ratio. The achieved ammonia coverage ratio estimation was applied to estimate the post-SCR NOx and NH3 concentrations. Simulation verification results under US06 cycle proved the effectiveness of the proposed method in accurately estimating the aforementioned key SCR states. The proposed observer can potentially be popularly applied to the production SCR systems for the advanced SCR control systems and on-board diagnostics.

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