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Language: English

Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received October 12, 2022
Revised January 6, 2023
Accepted January 31, 2023

Acknowledgements: This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) [NRF-2016R1A5A1009592]. The Institute of Engineering Research at Seoul National University provided research facilities for this work.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Model-based fault detecting strategy of urea-selective catalytic reduction (SCR) for diesel vehicles

Sanha Lim and Jong Min Lee^†

School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Korea

jongmin@snu.ac.kr

Korean Journal of Chemical Engineering, July 2023, 40(7), 1616-1622(7), 10.1007/s11814-023-1426-y

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Abstract

Selective catalytic reduction (SCR) is diesel aftertreatment using a reduction agent to reduce nitrogen oxides. Diesel engine regulations are being tightened; therefore, the diesel aftertreatment system should be operated efficiently. In the urea-SCR system, there is a possibility of various faults, e.g., catalyst deactivation by sulfur or hydrothermal aging and fault in urea injection system. These faults interfere with normal system operation and result in increase of NOx concentration at the tailpipe. To prevent this situation, it is necessary to detect system faults. In this study, a first-principle model for SCR system is presented based on mass and energy balance equations. Using the onedimensional urea-SCR model, this research introduces a model-based fault detecting strategy for SCR system. The residuals are calculated as the difference between the model calculation and the actual catalyst system measurement with the system faults. The results of this research are used in fault diagnosis and fault tolerant control studies to meet diesel vehicle nitrogen oxide regulations even in the presence of catalyst faults.

Keywords

Selective Catalytic Reduction Model-based Fault Detection Aftertreatment System Diesel Vehicle

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