An NOx Sensor-Based Direct Algebraic Approach-Newton Observer for Urea Selective Catalytic Reduction System State Estimations

[+] Author and Article Information
Qinghua Lin

Department of Mechanical Engineering, Tennessee Technological University, Cookeville, TN 38505

Pingen Chen

Department of Mechanical Engineering, Tennessee Technological University, Cookeville, TN 38505

1Corresponding author.

ASME doi:10.1115/1.4040221 History: Received November 18, 2017; Revised May 04, 2018


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 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 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 proposed method in accurately estimating the aforementioned key SCR states. The proposed observer can potentially be popularly applied to production SCR systems for advanced SCR control systems and on-board diagnostics.

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