Ammonia injection optimization for selective catalytic reduction aftertreatment systems

2020 ◽  
pp. 146808742093312
Author(s):  
Benjamin Pla ◽  
Pau Bares ◽  
Enrique Sanchis ◽  
André Aronis
Keyword(s):  
Optimal Control ◽  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Test Cycle ◽  
Injection Strategy ◽  
Potential Benefits ◽  
Standard Calibration ◽  
Emission Limits ◽  
Aftertreatment Systems ◽  
Ammonia Injection

This work presents an optimized ammonia injection strategy for the Worldwide Harmonized Light Vehicles Test Cycle and its potential benefits in terms of NO x emissions and ammonia consumption in selective catalytic reduction. An optimization tool based on optimal control was used to improve the ammonia injection in the selective catalytic reduction with different NO x emission limits. This optimal control can be used in two ways: one to minimize NO x emission and another to reduce the ammonia consumption in the selective catalytic reduction. The optimized strategy and the standard ammonia injection strategy were tested and compared on a fully instrumented engine test bench when applied in a Worldwide Harmonized Light Vehicles Test Cycle. The results showed a considerable improvement in the use of the optimization tool. When compared to the standard calibration, the new injection strategy for the same amount of ammonia injection reduced NO x emissions by 13.7%, and for the same NO x concentration emissions 33.5% of ammonia consumption was saved.

Comparative analysis on the effects of diesel particulate filter and selective catalytic reduction systems on a wide spectrum of chemical species emissions

2018 ◽  
Author(s):  
Z. Gerald Liu ◽  
Devin R. Berg ◽  
Thaddeus A. Swor ◽  
James J. Schauer‡
Keyword(s):  
Diesel Engine ◽  
Selective Catalytic Reduction ◽  
Diesel Particulate Filter ◽  
Catalytic Reduction ◽  
Wide Spectrum ◽  
Chemical Species ◽  
Pollutant Emissions ◽  
Particulate Filter ◽  
Diesel Particulate ◽  
Aftertreatment Systems

Two methods, diesel particulate filter (DPF) and selective catalytic reduction (SCR) systems, for controlling diesel emissions have become widely used, either independently or together, for meeting increasingly stringent emissions regulations world-wide. Each of these systems is designed for the reduction of primary pollutant emissions including particulate matter (PM) for the DPF and nitrogen oxides (NOx) for the SCR. However, there have been growing concerns regarding the secondary reactions that these aftertreatment systems may promote involving unregulated species emissions. This study was performed to gain an understanding of the effects that these aftertreatment systems may have on the emission levels of a wide spectrum of chemical species found in diesel engine exhaust. Samples were extracted using a source dilution sampling system designed to collect exhaust samples representative of real-world emissions. Testing was conducted on a heavy-duty diesel engine with no aftertreatment devices to establish a baseline measurement and also on the same engine equipped first with a DPF system and then a SCR system. Each of the samples was analyzed for a wide variety of chemical species, including elemental and organic carbon, metals, ions, n-alkanes, aldehydes, and polycyclic aromatic hydrocarbons, in addition to the primary pollutants, due to the potential risks they pose to the environment and public health. The results show that the DPF and SCR systems were capable of substantially reducing PM and NOx emissions, respectively. Further, each of the systems significantly reduced the emission levels of the unregulated chemical species, while the notable formation of new chemical species was not observed. It is expected that a combination of the two systems in some future engine applications would reduce both primary and secondary emissions significantly.

scholarly journals Selective Catalytic Reduction System Ammonia Injection Control Based on Deep Deterministic Policy Reinforcement Learning

2021 ◽  
Vol 9 ◽  
Author(s):  
Peiran Xie ◽  
Guangming Zhang ◽  
Yuguang Niu ◽  
Tianshu Sun
Keyword(s):  
Reinforcement Learning ◽  
Selective Catalytic Reduction ◽  
Virtual Environment ◽  
Flue Gas ◽  
Catalytic Reduction ◽  
Thermal Power ◽  
Gas Treatment ◽  
Intelligent Controller ◽  
Secondary Pollution ◽  
Ammonia Injection

The control of flue gas emission in thermal power plants has been a topic of concern. Selective catalytic reduction technology has been widely used as an effective flue gas treatment technology. However, precisely controlling the amount of ammonia injected remains a challenge. Too much ammonia not only causes secondary pollution but also corrodes the reactor equipment, while too little ammonia does not effectively reduce the NOx content. In recent years, deep reinforcement learning has achieved better results than traditional methods in decision making and control, which provides new methods for better control of selective catalytic reduction systems. The purpose of this research is to design an intelligent controller using reinforcement learning technology, which can accurately control ammonia injection, and achieve higher denitrification effect and less secondary pollution. To train the deep reinforcement learning controller, a high-precision virtual denitration environment is first constructed. In order to make the virtual environment more realistic, this virtual environment was designed as a special structure with two decoders and a unique approach was used in fitting the virtual environment. A deep deterministic policy agent is used as an intelligent controller to control the amount of injected ammonia. To make the intelligent controller more stable, the actor-critic framework and the experience pool approach were adopted. The results show that the intelligent controller can control the emissions of nitrogen oxides and ammonia at the outlet of the reactor after training in virtual environment.

It is no laughing matter: nitrous oxide formation in diesel engines and advances in its abatement over rhodium-based catalysts

2016 ◽  
Vol 6 (21) ◽  
pp. 7671-7687 ◽  
Author(s):  
Magdalena Jabłońska ◽  
Regina Palkovits
Keyword(s):  
Nitrous Oxide ◽  
Diesel Engine ◽  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Oxide Formation ◽  
Diesel Oxidation Catalysts ◽  
Diesel Oxidation ◽  
Ammonia Slip ◽  
Aftertreatment Systems ◽  
By Products

N2O appears as one of the undesired by-products in exhaust gases emitted from diesel engine aftertreatment systems, such as diesel oxidation catalysts (DOC), lean NOx trap (LNT, also known as NOx storage and reduction (NSR)) or selective catalytic reduction (NH3-SCR and HC-SCR) and ammonia slip catalysts (ASC, AMOX, guard catalyst).

scholarly journals A CFD Study on Flow Control of Ammonia Injection for Denitrification Processes of SCR Systems in Coal-Fired Power Plants

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1352
Author(s):  
Min-Gyu Kim ◽  
Deok-Cheol Seo ◽  
Hee-Taeg Chung
Keyword(s):  
Selective Catalytic Reduction ◽  
Flow Rate ◽  
Power Plants ◽  
Catalytic Reduction ◽  
Molar Ratio ◽  
Exhaust Gas ◽  
Two Dimensional ◽  
Inlet Conditions ◽  
Denitrification Process ◽  
Ammonia Injection

The selective catalytic reduction method is a useful method for the denitrification process of exhaust gas emitted from industrial facilities. The distribution of the ammonia–nitrogen oxide mixing ratio at the inlet of the catalyst layers is important in the denitrification process. In this study, a computational analysis technique was used to improve the uniformity of the NH3/NO molar ratio by controlling the flow rate of the ammonia injection nozzle according to the flow distribution of nitrogen oxides in the inlet exhaust gas of the denitrification facility. The application model was simplified to the two-dimensional array adopted from the existing selective catalytic reduction (SCR) process in the large-scaled coal-fired power plant. As the inlet conditions, four (4) types of flow pattern were simulated, i.e., parabolic, upper-skewed, lower-skewed, and random. The flow rate of the eight (8) nozzles installed in the ammonia injection grid was controlled by Design Xplorer as the optimization tool. In order to solve the two-dimensional steady, incompressible, and viscous flow fields, the commercial software named ANSYS Fluent was used with the κ-ε turbulence model. The root mean square of NH3/NO molar ratio at the inlet of the catalyst layer has been improved from 84.6% to 90.1% by controlling the flow rate of the ammonia injection nozzles. From the present numerical simulation, the operation guide could be drawn for the ammonia injection nozzles in SCR DeNOx facilities.

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