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.

Backstepping Based Nonlinear Ammonia Surface Coverage Ratio Control for Diesel Engine Selective Catalytic Reduction Systems

2009 ◽  
Author(s):  
Ming Feng Hsieh ◽  
Junmin Wang
Keyword(s):  
Diesel Engine ◽  
System Dynamics ◽  
Selective Catalytic Reduction ◽  
Surface Coverage ◽  
Catalytic Reduction ◽  
Control Law ◽  
Ammonia Emissions ◽  
Coverage Ratio ◽  
Cycle Simulation ◽  
Scr System

This paper presents an ammonia surface coverage ratio control approach based on the backstepping concept for diesel engine selective catalytic reduction (SCR) systems. SCR models with multiple cells connected in cascade provide more accurate representations of the actual SCR system dynamics by considering the spatial distribution. Control of SCR system ammonia coverage ratio is critically important and effective in terms of ensuring low tailpipe NOx and ammonia emissions. However, such a task is also very challenging primarily due to the nonlinearities of the SCR dynamics and limited ammonia injection control authority. Grounded in the understanding of the SCR nonlinear dynamic characteristics, a backstepping-based nonlinear control law is then proposed to regulate the ammonia surface coverage ratio of the last SCR cell in order to tightly control the tailpipe NOx and ammonia emissions. Lyapunov-based analyses show the stability of the designed control law. FTP75 test cycle simulation results based on a full-vehicle (including engine, chassis, and aftertreatment systems) model illustrated that, compared with a conventional PID controller, the nonlinear backstepping control law can more appropriately handle the SCR system dynamics and exhibits superior ammonia coverage ratio control capability.

Robust Filtering for Ammonia Coverage Estimation in Diesel Engine Selective Catalytic Reduction Systems

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Hui Zhang ◽  
Junmin Wang ◽  
Yue-Yun Wang
Keyword(s):  
Diesel Engine ◽  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Critical Role ◽  
Approximation Error ◽  
Ammonia Concentration ◽  
Nonlinear Observer ◽  
Coverage Ratio ◽  
Vehicle Simulation ◽  
Measurement Noises

In this paper, we investigate the nonlinear observer designs to estimate the ammonia coverage ratio in the diesel engine selective catalytic reduction (SCR) systems. The ammonia coverage ratio is an important variable due to its critical role in the SCR NOx conversion and the ammonia slip. However, the ammonia coverage ratio cannot be directly measured by onboard sensors. Therefore, it is necessary to develop effective observers to estimate the ammonia coverage ratio online. Based on a three-state SCR model, we develop two nonlinear observers. The first one only employs the dynamics of the ammonia concentration. The structure and the algorithm are simple. But it is sensitive to the measurement noises and the uncertainties in the system parameters. The second one is a discrete-time smooth variable structure estimator which is robust to the measurement noises, the approximation error, and the system uncertainties. Both estimators are implemented on a full-vehicle simulation of the FTP75 test cycle. The simulation results have verified the theoretical analysis.

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

Sliding-mode control of automotive selective catalytic reduction systems with state estimation

2019 ◽  
Vol 234 (2-3) ◽  
pp. 630-644
Author(s):  
Yao Ma ◽  
Junmin Wang
Keyword(s):  
Selective Catalytic Reduction ◽  
Surface Coverage ◽  
Sliding Mode ◽  
Catalytic Reduction ◽  
Tracking Error ◽  
Estimation Accuracy ◽  
Sliding Mode Controller ◽  
Coverage Ratio ◽  
Implementation Purpose ◽  
Ammonia Slip

A sliding-mode controller for an automotive selective catalytic reduction system is designed to drive its ammonia surface coverage ratio to the target level. The proposed controller only requires NOx, temperature and air flow sensor measurement installed on most mass production vehicles. Selective catalytic reduction systems have been widely equipped on diesel-powered ground vehicles to remove excessive NOx emissions. The tradeoff between NOx removal efficiency and ammonia slip poses a control challenge on regulating the ammonia surface coverage ratio to a proper level in the presence of disturbance. In this study, a sliding-mode controller is designed with explicit consideration of measurement noise and actuator saturation. The finite time convergence of tracking error is proved by a Lyapunov approach. For implementation purpose, an observer of ammonia surface coverage ratio and ammonia slip is also designed to provide states feedback and fault diagnostic information. The closed-loop controller performance is evaluated under an urban driving scenario based on an experimentally validated model. Results demonstrate the robust tracking performance and estimation accuracy against bounded uncertainties. The overall NOx efficiency is maintained with an acceptable ammonia slip level during the transient test cycle FTP75.

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