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Sustainability 2016, 8(5), 478; doi:10.3390/su8050478

Modeling and Multi-Objective Optimization of NOx Conversion Efficiency and NH3 Slip for a Diesel Engine

1,2
,
1,2
,
1,2,* , 1,2,3
and
1,2
1
Wuhan University of Technology, Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan 430070, China
2
Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan 430070, China
3
Mechanical Engineering Department, Ho Polytechnic, P. O. Box HP 217, Ho 036, Ghana
*
Author to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 8 April 2016 / Revised: 9 May 2016 / Accepted: 10 May 2016 / Published: 17 May 2016
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Abstract

The objective of the study is to present the modeling and multi-objective optimization of NOx conversion efficiency and NH3 slip in the Selective Catalytic Reduction (SCR) catalytic converter for a diesel engine. A novel ensemble method based on a support vector machine (SVM) and genetic algorithm (GA) is proposed to establish the models for the prediction of upstream and downstream NOx emissions and NH3 slip. The data for modeling were collected from a steady-state diesel engine bench calibration test. After obtaining the two conflicting objective functions concerned in this study, the non-dominated sorting genetic algorithm (NSGA-II) was implemented to solve the multi-objective optimization problem of maximizing NOx conversion efficiency while minimizing NH3 slip under certain operating points. The optimized SVM models showed great accuracy for the estimation of actual outputs with the Root Mean Squared Error (RMSE) of upstream and downstream NOx emissions and NH3 slip being 44.01 × 10−6, 21.87 × 10−6 and 2.22 × 10−6, respectively. The multi-objective optimization and subsequent decisions for optimal performance have also been presented. View Full-Text
Keywords: NOx conversion efficiency; NH3 slip; genetic algorithm; support vector machine; prediction model; multi-objective optimization NOx conversion efficiency; NH3 slip; genetic algorithm; support vector machine; prediction model; multi-objective optimization
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Liu, B.; Yan, F.; Hu, J.; Turkson, R.F.; Lin, F. Modeling and Multi-Objective Optimization of NOx Conversion Efficiency and NH3 Slip for a Diesel Engine. Sustainability 2016, 8, 478.

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