Lean Breakthrough Phenomena Analysis for TWC OBD on a Natural Gas Engine using a Dual-Site Dynamic Oxygen Storage Capacity Model

2017-01-0962

03/28/2017

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Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
Oxygen storage capacity (OSC) is one of the most critical characteristics of a three-way catalyst (TWC) and is closely related to the catalyst aging and performance. In this study, a dynamic OSC model involving two oxygen storage sites with distinct kinetics was developed. The dual-site OSC model was validated on a bench reactor and a natural gas engine. The model was capable of predicting temperature dependence on OSC with H2, CO and CH4 as reductants. Also, the effects of oxygen concentration and space velocity on the amount of OSC were captured by the model.
The validated OSC model was applied to simulate lean breakthrough phenomena with varied space velocities and oxygen concentrations. It is found that OSC during lean breakthrough is not a constant for a particular TWC catalyst and is dependent on space velocity and oxygen concentration. Specifically, breakthrough time exhibits a non-linear, inverse correlation to oxygen flux. Breakthrough OSC increases slightly with oxygen concentration and increases significantly as space velocity decreases. Moreover, at high space velocities, the majority of breakthrough OSC is from the PGM-ceria surface site (kinetically controlled). At low space velocities, there is a substantial amount of breakthrough OSC from the sub-surface ceria site (diffusion controlled). Correlations of breakthrough time and breakthrough OSC as a function of oxygen concentration and space velocity were established. An alternative methodology of TWC OBD with the use of developed correlations was presented and discussed.
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DOI
https://doi.org/10.4271/2017-01-0962
Pages
10
Citation
Gong, J., Wang, D., Brahma, A., Li, J. et al., "Lean Breakthrough Phenomena Analysis for TWC OBD on a Natural Gas Engine using a Dual-Site Dynamic Oxygen Storage Capacity Model," SAE Technical Paper 2017-01-0962, 2017, https://doi.org/10.4271/2017-01-0962.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-0962
Content Type
Technical Paper
Language
English