2022-Global Kinetic Modeling of a Commercial DOC Based on a Reduced Synthetic Gas Bench Protocol

2022-01-0558

03/29/2022

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
Various techniques are constantly being devised to accelerate model generation leading to shorter product development cycle. This work proposes and implements a reduced synthetic gas bench (SGB) test protocol for a commercial Pt-Pd diesel oxidation catalyst (DOC) that can be used to develop global reaction kinetics. The kinetics thus developed were implemented in a 1D model to predict DOC emissions accurately over a wide operating window. Hydrocarbons (HCs) in the exhaust were categorized as Propylene (C3H6) representing partially oxidized hydrocarbons and n-Decane (C10H22) representing unburnt fuel. Test protocols were defined using the order of inhibition of the various species present in the exhaust, namely, CO, NOx (NO+NO2) and HC for the specific reaction under consideration. The oxidation reactions for CO and HCs were found to be inhibited competitively by CO and HCs; both the NOx species inhibited these reactions to the same extent. The NO oxidation reaction was found to be heavily inhibited by the hydrocarbons. In addition to the oxidation kinetics (by O2 and NO2), and the N2O formation kinetics, nitrate storage and release kinetics were modeled to account for scenarios with high NO2 at low temperature. Simple root mean square error (RMSE) based objective function definition was used to fit the experimental data and generate reaction kinetics. The reaction kinetics thus developed were validated with (a) simulated multispecies datasets collected on gas bench representing various engine out exhaust gas mixtures and (b) using transient engine dynomometer data.
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DOI
https://doi.org/10.4271/2022-01-0558
Pages
7
Citation
Desai, C., Kadam, V., Chowdhury, K., Vernham, B. et al., "2022-Global Kinetic Modeling of a Commercial DOC Based on a Reduced Synthetic Gas Bench Protocol," SAE Technical Paper 2022-01-0558, 2022, https://doi.org/10.4271/2022-01-0558.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0558
Content Type
Technical Paper
Language
English