Optimization of the ammonia coverage ratio references in diesel engine two-can selective catalytic reduction systems via nonlinear model predictive control. (October 2014)

• Record Type: Journal Article
• Authors: Zhang, Hui; Wang, Junmin; Wang, Yue-Yun
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 228:Number 12(2014:Dec.)
• Page Start: 1452
• Page End: 1467
• Publication Date: 2014-10
• Subjects: Diesel engine emissions -- selective catalytic reduction -- system modeling and identification -- automotive systems -- nonlinear model predictive control -- ammonia coverage ratio optimization; Mechanical engineering -- Congresses; Transportation engineering -- Congresses; 629.2
• DOI: 10.1177/0954407014532791
• Languages: English
• ISSNs: 0954-4070

Abstract

In this work, we investigate the driving-cycle-based ammonia coverage ratio reference optimization for diesel engine two-can selective catalytic reduction systems. The ammonia coverage ratio references are the desired profiles of the ammonia coverage ratios. As these desired profiles can be set as the references for the feedback controls, it is important to obtain their optimal values. The model development and system parameter identification for these two catalyst cans are carried out by considering the main chemical reactions inside the catalyst cans and using the experimental data from the US06 test driving cycle. The main advantage of the two-can setup is twofold: the first catalyst can is mainly used to reduce the nitrogen oxides; the second catalyst can is used to adsorb the ammonia emitted from the first can such that the nitrogen oxides are reduced and the undesired ammonia slip is constrained. For high nitrogen oxide conversion, it is intuitively required that the ammonia coverage ratio for the first catalyst can is as high as possible. However, a high ammonia coverage ratio increases the ammonia slip downstream. In order to constrain the ammonia slip downstream, it is expected that the ammonia coverage ratio for the second catalyst can is as low as possible. However, the lower ammonia coverage ratio may not help nitrogen oxide reduction in the second can. Because of the conflict in the ammonia coverage ratios for these two catalyst cans, it is quite interesting and meaningful to study the optimal ammonia coverage ratios. With the developed system models, we propose a nonlinear model predictive control approach to solve the optimization problem. Various cases are studied to investigate the effect of the initial value on the ammonia coverage ratios. Compared with the existing results, the obtained ammonia injection profile which decides the ammonia coverage ratios can achieve much better control performance with respect to the tailpipe nitrogen oxide reduction and ammonia slip.