Nonlinear model predictive control applied to multivariable thermal and chemical control of selective catalytic reduction aftertreatment

Jonathan Sowman, Dina Shona Laila, Peter Fussey, Anthony Truscott, Andrew Cruden

Research output: Contribution to journalArticle

2 Citations (Scopus)
42 Downloads (Pure)

Abstract

Manufacturers of diesel engines are under increasing pressure to meet progressively stricter NO x emission limits. A key NO x abatement technology is selective catalytic reduction in which ammonia, aided by a catalyst, reacts with NO x in the exhaust stream to produce nitrogen and water. The conversion efficiency is temperature dependent: at low temperature, reaction rates are temperature limited, resulting in suboptimal NO x removal, whereas at high temperatures, they are mass transfer limited. Maintaining sufficiently high temperature to allow maximal conversion is a challenge, particularly after cold start, as well as during conditions in which exhaust heat is insufficient, such as periods of low load or idling. In this work, a nonlinear model predictive controller simultaneously manages urea injection and power to an electric catalyst heater, in the presence of constraints.

Original languageEnglish
Pages (from-to)1017-1024
Number of pages8
JournalInternational Journal of Engine Research
Volume20
Issue number10
Early online date26 Jun 2019
DOIs
Publication statusPublished - 1 Dec 2019

Keywords

  • Model predictive control
  • diesel aftertreatment controls
  • selective catalytic reduction

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering

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