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CFD Modeling of Tailpipe NOx Sensor Accuracy
Journal Article
03-11-04-0029
ISSN: 1946-3936, e-ISSN: 1946-3944
Sector:
Topic:
Citation:
Kalyankar, A., Munnannur, A., and Liu, Z., "CFD Modeling of Tailpipe NOx Sensor Accuracy," SAE Int. J. Engines 11(4):435-446, 2018, https://doi.org/10.4271/03-11-04-0029.
Language:
English
Abstract:
In a modern diesel aftertreatment system, a sensor for nitrogen oxides (NOx)
placed downstream of the selective catalytic reduction (SCR) catalyst is
necessary to determine if the tailpipe NOx concentration remains below the
applicable On-board diagnostic (OBD) threshold. Typically the same NOx sensor
also provides feedback to the dosing control module to adjust diesel exhaust
fluid (DEF) dosing rate thereby controlling tailpipe NOx and ammonia emissions.
However, feedback signal sent by the tailpipe NOx sensor may not always be
accurate due to reasons including non-uniformity in NOx and ammonia
distributions at SCR outlet. Flow based metrics from computational fluid
dynamics (CFD) analyses, that are typically used to qualitatively assess NOx
sensor accuracy in different designs are often inadequate. In this work, an
improved CFD analysis procedure has been developed for assessing NOx sensor
accuracy. This approach enables a direct comparison of NOx sensor accuracy
between different sampling probe and sensor designs. This improved modeling
approach was first validated against test data without spray effects by
injecting gaseous NOx in a 5″ pipe. The impact of various numerical and
geometrical sensitivities on model predictions was considered. Afterwards,
studies were conducted to study the impact of non-uniformity of NOx and velocity
distribution on sensor accuracy. Species distribution index
(SDI) and hole and hole mass flow gamma
(γ) were found to be useful metrics directly affecting NOx
sensor accuracy. Lastly, the modeling approach was validated against test data
on a representative aftertreatment system. Model predictions of sensor accuracy
error were in agreement with test data (<5% error) at multiple operating
points for two different sensor designs.