Model-based Analysis of the Oscillatory NO x in Urea Selective Catalytic Reduction Systems

2017-32-0107

11/05/2017

Features
Event
JSAE/SAE Small Engine Technologies Conference & Exhibition
Authors Abstract
Content
The urea-water-solution based selective catalyst reduction (SCR) system is one of the effective devices for reduction of NOx from diesel engines. In an effort to understand the various levels of oscillation observed in the NOx measurement downstream of a SCR in which the urea dosage is controlled by a crankshaft-link pump, a zero-dimensional dynamic SCR model is developed in this paper based on conservation of mass. The model contains three states including the concentrations of NOx and ammonia in the SCR and the surface coverage rate of the catalyst. The temperature-dependent reactions considered in the model include the adsorption, desorption and oxidation of ammonia and the NOx reduction with the reaction constants provided by the catalyst company. The dynamic SCR model is validated both at steady state and during transient under various engine operating conditions and urea dosing rates. A periodic modulation of the urea dosing rate is adopted to simulate the periodic urea supply resulted from the reciprocating motion of the crankshaft-link pump. The simulation results exhibit similar oscillatory behaviors in the NOx concentration as observed in the experimental measurement, which is further analyzed and explained based on the nonlinear characteristics between the downstream NOx and the ammonia dosage. Based on the interpretation of the oscillatory NOx signal, an algorithm for identification of the cross-sensitivity of the smart NOx sensor to ammonia is proposed.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-32-0107
Pages
7
Citation
Chou, C., Kuo, T., Tsai, T., Su, Y. et al., "Model-based Analysis of the Oscillatory NO x in Urea Selective Catalytic Reduction Systems," SAE Technical Paper 2017-32-0107, 2017, https://doi.org/10.4271/2017-32-0107.
Additional Details
Publisher
Published
Nov 5, 2017
Product Code
2017-32-0107
Content Type
Technical Paper
Language
English