RESEARCH ARTICLE


Dynamic Model Parameter Identification and Simulation of SCR Based on Genetic Algorithm§



Ren Hongjuan1, 2, Lou Diming1, *, Zhu Jian2, Luo Yiping2
1 College of Automotive Studies, Tongji University, Shanghai, 201620, P.R. China
2 School of Automotive Engineering, Shanghai University of Engineering Science, Shanghai, 201620, P.R. China


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Creative Commons License
© 2015 Hongjuan et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the College of Automotive Studies, Tongji University, Shanghai, 201620, P.R. China; E-mail: loudiming@tongji.edu.cn
§ Foundation Item: China 863 fund “Research on the key technology of diesel engine after-treatment to meet Euro emission standard VI” (2012AA 111717)


Abstract

The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.

Keywords: AVL boost, GA, parameter identificationC, SCR.