A urea decomposition modeling framework for SCR systems

Thomas L. McKinley, Andrew G Alleyne

Research output: Contribution to journalArticle

Abstract

Selective catalytic reduction (SCR) is allowing diesel engines to reach NOx emission levels which are unachievable in-cylinder. This technology is still evolving, and new catalyst formulations which provide higher performance and greater durability continue to be developed. Usually, their performance is measured on a flow reactor using ammonia as the reductant. However, in mobile applications a urea-water solution is used instead, and urea decomposition by thermolysis and hydrolysis provides the required ammonia to the catalyst. It is well known that urea decomposition is incomplete by the inlet face of the converter, and this is at least one reason why on-engine performance is generally lower than would be expected from reactor tests. Previous modeling of urea-water droplets has focused on developing detailed sub-models that can be implemented into computational fluid dynamics (CFD) codes. However, the required computational effort is not compatible with real-time, controls-oriented models. This paper addresses that gap by presenting a framework for urea-decomposition modeling which employs the so-called probability distribution function (PDF) operator method. As a starting point, this paper focuses on operators of atomization, particle-borne decomposition, and catalyst impact. Furthermore, the significance of these effects are reported over a span of temperatures and space velocities. The framework is quite general and provides a means for integrating detailed droplet models, three-dimensional CFD codes, and experimental measurements. Moreover, the approach can be applied to other two-phase flow arrangements such as fuel injection upstream of fuel reformers and diesel oxidation catalysts (DOCs).

Original languageEnglish (US)
Pages (from-to)612-626
Number of pages15
JournalSAE Technical Papers
DOIs
StatePublished - Jan 1 2009

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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