An adaptive control strategy for urea-SCR aftertreatment system

Meisami‐Azad, Mona; Mohammadpour, Javad; Grigoriadis, Karolos; Harold, Michael P.

doi:10.1109/acc.2010.5531224

Cited by 16 publications

(8 citation statements)

References 10 publications

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“…The gaseous isocyanic acid is then converted into gaseous ammonia on the catalyst as in (3). Thus Urea Thermal Decomposition NH 2 − CO − NH 2 (l or g) → NH 3 (g) + HN CO(g) (2) Isocyanic Acid Hydrolysis The injected urea, which is in fine droplets, is mixed with the exhaust flow and based on the flow properties, the conversion efficiency (based on exhaust temperature and space velocity), the mixing time constant, the characteristic mixing length and the distance from the urea dosing system to the catalyst face, the flow of ammonia, and isocyanic acid entering the SCR catalyst is estimated using a reduced-order dynamic system model. This model is an important part of the overall SCR control approach since it provides the amount of ammonia and isocyanic acid entering the SCR catalyst.…”

Section: A Hydrolysis Modelmentioning

confidence: 99%

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Experimental Demonstration of Ammonia Storage and Slip Modeling With Control for an SCR Aftertreatment System

Ofoli

2014

IEEE Trans. on Ind. Applicat.

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Emission control is currently one of the biggest challenges and concerns in the automotive industry for cleaner diesel engines. Due to the low level of NO x emission enforced by the Environmental Protection Agency (EPA), selective catalytic reduction (SCR) technology is currently one of the most feasible solutions. SCR technology uses diesel exhaust fluid (DEF), which is a urea solution of 32.7% urea with 67.3% water to reduce NO x emission. The urea solution is converted to ammonia (NH 3 ), which reacts with NO x over a catalyst to form N 2 and water. In this paper, a practical and dynamic model for modeling and controlling ammonia surface coverage or storage on an SCR system with a vanadia-based catalyst is implemented. It also included modeling of NH 3 slip. This work was implemented on an electronic control module and tested on a medium-duty diesel engine. The improved NO x efficiencies observed with the corresponding reduction in urea usage illustrate a successful solution, indicating that this new dynamic modeling of ammonia surface coverage and its effective usage to manage urea dosing is a valuable tool for SCR aftertreatment systems.

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Section: A Hydrolysis Modelmentioning

confidence: 99%

“…Different SCR control strategies involving adaptive control [2] and model-predictive control [3] have been investigated in the literature. These techniques are complex to calibrate on 0093-9994 © 2014 IEEE.…”

Section: Introductionmentioning

confidence: 99%

Experimental Demonstration of Ammonia Storage and Slip Modeling With Control for an SCR Aftertreatment System

Ofoli

2014

IEEE Trans. on Ind. Applicat.

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“…Also, a comparison between NO x and NH 3 sensors-based strategies was shown to conclude that the use of NH 3 sensors, instead of NO x sensor, provides better results for European transient cycle. Another paper by Meisami-Azad, et al (2010) implemented a state/output feedback controller using linear parameter varying (LPV) design for urea-SCR reduction after-treatment system. Feedback control using state observer was shown to require more computational effort compared to strategy based on sensor feedback only.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Ammonia Injection for Emissions Control in Power Plants

et al. 2015

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One of the effective devices to reduce NO x in power plants is the ammonia based selective catalyst reduction (SCR) system. In this paper, kinetic SCR model simulator is tuned and validated with representative site data from an actual combined-cycle power plant. This simulator is then used for the development and implementation of model predictive control (MPC) for SCR systems to control the plant startup NO x emissions along with maintaining ammonia slip within the acceptable limit. Also, the results of linear and nonlinear MPC are compared. The startup NO x reduction obtained in both cases is seen to be close to ~85%, but the computational effort required for both these approaches differ significantly.

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“…Control systems have been developed and evaluated for emission control on boilers, power plants and automobiles. Research efforts have been directed in the area of monitoring [114], estimation [115][116][117], cascade control [118], adaptive control [119,120], model-based feedback control [121][122][123][124], linear MPC [125,126] and nonlinear MPC [127,128].…”

Section: Emission and Effluent Managementmentioning

confidence: 99%