A predictive control approach to diesel Selective Catalytic Reduction

2015 ◽  
Author(s):  
J. Sowman ◽  
D. S. Laila ◽  
A. J. Cruden ◽  
P. Fussey ◽  
A. Truscott
Keyword(s):  
Selective Catalytic Reduction ◽  
Predictive Control ◽  
Catalytic Reduction ◽  
Control Approach

Characteristics-based model predictive control of selective catalytic reduction in diesel-powered vehicles

2016 ◽  
Vol 47 ◽  
pp. 98-110 ◽  
Author(s):  
H. Pakravesh ◽  
I. Aksikas ◽  
M. Votsmeier ◽  
S. Dubljevic ◽  
R.E. Hayes ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Selective Catalytic Reduction ◽  
Predictive Control ◽  
Catalytic Reduction

Diesel Engine Selective Catalytic Reduction (SCR) Ammonia Surface Coverage Control Using a Computationally-Efficient Model Predictive Control Assisted Method

2009 ◽  
Author(s):  
Ming Feng Hsieh ◽  
Junmin Wang
Keyword(s):  
Diesel Engine ◽  
Model Predictive Control ◽  
Selective Catalytic Reduction ◽  
Predictive Control ◽  
Surface Coverage ◽  
Catalytic Reduction ◽  
Computationally Efficient ◽  
Coverage Ratio ◽  
Control Objective ◽  
Control Authority

This paper presents a diesel engine selective catalytic reduction (SCR) control design based on a novel model predictive control (MPC)-assisted approach, which utilizes the advantages of MPC while keeping the computation demand under an acceptable level. The SCR control problem is featured by the challenges of time delay, significant time-varying characteristics, and limited control authority. Based on the understanding of the SCR reactions, the NH3 surface coverage ratio was selected as the control objective. The proposed MPC-assisted method was compared with conventional controllers such as PID and linear MPC (LMPC). Simulation results exhibited that the MPC-assisted approach can achieve a SCR ammonia surface coverage ratio control with much smaller root mean square error compared to these of other controllers while maintaining a manageable computational demand, and in turn better control of tailpipe NOx and ammonia emissions.

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