Blucher Engineering Proceedings

Setembro 2016, vol.3, num.1 - XXIV Simpósio Internacional de Engenharia Automotiva
<strong>Menção Honrosa</strong> - Open Access Idioma principal | Segundo principal

CFD effectiveness of AUS32 crystallization prediction in SCR systems

Eficiência do CFD na predição da cristalização de Ureia em sistemas SCR

SOUZA, Anderson de Almeida; GLOVASKI, Leandro Seizo; SILVA, Roberto Carlos de Castro

<strong>Menção Honrosa</strong>:

Diesel engine technology has been driven by stringent regulation. To fulfill these demands emission control systems are constantly improving. In this context exhaust gas aftertreatment development assumes an important role.

Due to emissions standards evolution which considerably reduced the limits for hazardous gases, NOx from engine combustion chamber included, some vehicles are equipped with an aqueous solution of urea (Arla32) dosing system in order to reduce, when working with a SCR (Selective Catalyst Reduction) catalyst, NOx emissions level. SCR aftertreatment system operates by dosing Arla32 inside the exhaust pipe, getting it converted to ammonia by chemical reactions and, when in contact to the catalytic material (SCR), transforms NOx molecules to Nitrogen and water. But some factors can make that part of the dosed urea solution does not convert into ammonia. The accumulation of urea and its subcomponents inside the piping causes crystallization. Exhaust systems with high level of crystallization leads to efficiency loss of NOx conversion, ammonia emission increase and vehicle performance loss due to exhaust backpressure increasing. In order to avoid the urea crystallization in vehicles equipped with Arla32 dosing system, CFD simulations are made even before a prototype sample is available. Usually, CFD analysis is performed in some operating points, in steady state condition for a short period of time. The goal of this paper is to evaluate the results obtained in CFD simulation by comparing to results in real systems tested in dynamometer.

Diesel engine technology has been driven by stringent regulation. To fulfill these demands emission control systems are constantly improving. In this context exhaust gas aftertreatment development assumes an important role.

Due to emissions standards evolution which considerably reduced the limits for hazardous gases, NOx from engine combustion chamber included, some vehicles are equipped with an aqueous solution of urea (Arla32) dosing system in order to reduce, when working with a SCR (Selective Catalyst Reduction) catalyst, NOx emissions level. SCR aftertreatment system operates by dosing Arla32 inside the exhaust pipe, getting it converted to ammonia by chemical reactions and, when in contact to the catalytic material (SCR), transforms NOx molecules to Nitrogen and water. But some factors can make that part of the dosed urea solution does not convert into ammonia. The accumulation of urea and its subcomponents inside the piping causes crystallization. Exhaust systems with high level of crystallization leads to efficiency loss of NOx conversion, ammonia emission increase and vehicle performance loss due to exhaust backpressure increasing. In order to avoid the urea crystallization in vehicles equipped with Arla32 dosing system, CFD simulations are made even before a prototype sample is available. Usually, CFD analysis is performed in some operating points, in steady state condition for a short period of time. The goal of this paper is to evaluate the results obtained in CFD simulation by comparing to results in real systems tested in dynamometer.

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DOI: 10.5151/engpro-simea2016-PAP85

Referências bibliográficas
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  • [3] BIRKHOLD, F., et al., Analysis of the Injection of Urea-Water-Solution for Automotive SCR DeNOx-Systems: Modeling of Two-Phase Flow and Spray/Wall-Interaction, 2006, SAE International.
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Como citar:

SOUZA, Anderson de Almeida; GLOVASKI, Leandro Seizo; SILVA, Roberto Carlos de Castro; "CFD effectiveness of AUS32 crystallization prediction in SCR systems", p-646-663. In: Anais do XXIV Simpósio Internacional de Engenharia Automotica - SIMEA 2016 [=Blucher Engineering Proceedings].. São Paulo: Blucher, 2016.
ISSN 23577592, DOI 10.5151/engpro-simea2016-PAP85

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