Model Based Analysis and Control Design of a Urea-SCR deNOx Aftertreatment System

2005 ◽  
Vol 128 (3) ◽  
pp. 737-741 ◽  
Author(s):  
Devesh Upadhyay ◽  
Michiel Van Nieuwstadt
Keyword(s):  
Sliding Mode ◽  
Catalytic Reduction ◽  
Nox Reduction ◽  
Control Design ◽  
Observer Design ◽  
Lumped Parameter Model ◽  
Control Synthesis ◽  
Model Based ◽  
Ammonia Slip ◽  
Controllability And Observability

In this paper we tackle issues relevant to model based control design for a Urea based Selective Catalytic Reduction (SCR) process relevant to automotive applications. A three state, control oriented, lumped parameter model of the system is used to investigate essential controllability and observability properties of the Urea-SCR plant. Results from the controllability and observability analysis of both nonlinear and linearized models are shown to have realistic implications. Observer design for predicting gas phase ammonia slip is outlined and results presented. An altered definition of the catalyst efficiency is used in control design. It is shown that this altered definition lends itself readily to control synthesis in the Sliding Mode framework while satisfying the dual control objectives of maximizing NOx reduction and minimizing ammonia slip.

Control Design of an Automotive Urea SCR Catalyst

2002 ◽  
Author(s):  
Devesh Upadhyay ◽  
Michiel Van Nieuwstadt
Keyword(s):  
Ammonia Oxidation ◽  
Catalytic Reduction ◽  
Nox Reduction ◽  
Control Design ◽  
Reaction Rates ◽  
Lumped Parameter Model ◽  
Lean Burn ◽  
Ammonia Sensing ◽  
Injection Process ◽  
Lean Nox

The leading aftertreatment technologies for NOx removal from the exhaust gas of lean burn engines, Diesels in particular, are urea based Selective Catalytic Reduction (SCR), Lean NOx Traps (LNT) and Active Lean NOx Catalysts (ALNC). It is generally believed that the SCR technique has the potential of providing the best NOx conversion efficiency relative to the other techniques. Nonetheless, it is crucial that the high conversion efficiencies be achieved with a minimum slippage of unreacted ammonia as tail pipe emissions. This necessitates a precise control over the urea injection process. The complex behavior of the catalyst substrate with respect to adsorption and desorption of ammonia in conjunction with a lack of “stored ammonia” sensing capabilities makes the control problem challenging. In this paper we present a model-based control design approach using a lumped parameter model of an SCR system that includes the essential dynamics of the plant. The model includes the adsorption, desorption and surface coverage dynamics, along with the NOx reduction and ammonia oxidation dynamics based on the relevant chemical reaction rates.

Investigation on the Control Strategy for Marine Selective Catalytic Reduction System

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Youhong Xiao ◽  
Hui Zhao ◽  
Xinna Tian ◽  
Wenyang Tan
Keyword(s):  
Optimal Control ◽  
Sliding Mode Control ◽  
Selective Catalytic Reduction ◽  
Control Strategy ◽  
Sliding Mode ◽  
Catalytic Reduction ◽  
Nox Reduction ◽  
Operating Conditions ◽  
Model Based ◽  
Mode Control

Selective catalytic reduction (SCR) system has been proven to be an effective technology for the removal of NOx emitted from marine diesel engines. In order to comply with stringent International Maritime Organization (IMO) Tier III NOx emission regulations, a number of engine manufacturers have developed their own SCR systems. This paper focuses on modeling of an SCR reactor and developing model-based urea dosing control strategy. A mathematical model of SCR reactors has been established. Model-based control strategy relies on the three-state and one-state reactor models established to accomplish urea dosing algorithm and is promising in limiting excessive NH3 slip. The SCR reactor model is further used in a simulation for the purpose of developing model-based urea dosing control strategies. The simulation results show that the NO sliding mode control requires a massive prestudy of the NOx reduction capability of the catalyst in order to set an appropriate control objective for each operating condition. However, this calibration work can be omitted in the optimal control and NH3 sliding mode control, which mitigates the workload of the controller design. The optimal control strategy presents a satisfied control performance in limiting NH3 slip during transient state engine operating conditions.

Nonlinear observer based sliding mode control and oxygen fraction estimation for diesel engine

2017 ◽  
Vol 40 (7) ◽  
pp. 2227-2239 ◽  
Author(s):  
Haoping Wang ◽  
Qiankun Qu ◽  
Yang Tian
Keyword(s):  
Diesel Engine ◽  
Sliding Mode Control ◽  
Oxygen Concentration ◽  
Control Method ◽  
Sliding Mode ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Model Based ◽  
Mode Control

In this paper, a nonlinear observer based sliding mode control (NOSMC) approach for air-path and a model-based observer for oxygen concentration in the diesel engine equipped with a variable geometry turbocharger and exhaust gas recirculation is introduced. We propose a less conservative observer design technique for Lipschitz nonlinear systems using Ricatti equations. The observer gains are obtained by solving the linear matrix inequality (LMI). Then a robust nonlinear control method, sliding mode control is applied for the states of intake and exhaust manifold pressure and compressor mass flow rate for the sake of the minimization of emissions. The proposed NOSMC controller is applied on a mean value model of turbocharged diesel engine. Besides this, a model-based observer is developed to estimate the oxygen concentration in the intake and exhaust manifolds owing to its significance in reducing emissions of diesel engines. The validation and efficiency of the proposed method are demonstrated by AMESim and Matlab/Simulink co-simulation results.

scholarly journals The Development and Implementation of Model-Based Control Algorithm of Urea-SCR Dosing System for Improving De-NOx Performance and Reducing NH3-Slip

2011 ◽  
Author(s):  
Soo-Jin Jeong ◽  
Woo-Seung Kim ◽  
Jung-Kwon Park ◽  
Ho-Kil Lee ◽  
Se-Doo Oh
Keyword(s):  
Control Algorithm ◽  
Catalytic Reduction ◽  
Fluid Model ◽  
Nox Reduction ◽  
Reaction Model ◽  
Urea Solution ◽  
Model Based Control ◽  
Model Based ◽  
Nh3 Emission ◽  
Scr System

The selective catalytic reduction (SCR) system is a highly-effective aftertreatment device for NOx reduction of diesel engines. Generally, the ammonia (NH3) was generated from reaction mechanism of SCR in the SCR system using the liquid urea as the reluctant. Therefore, the precise urea dosing control is a very important key for NOx and NH3 slip reduction in the SCR system. This paper investigated NOx and NH3 emission characteristics of urea-SCR dosing system based on model-based control algorithm in order to reduce NOx. In the map-based control algorithm, target amount of urea solution was determined by mass flow rate of exhaust gas obtained from engine rpm, torque and O2 for feed-back control NOx concentration should be measured by NOx sensor. Moreover, this algorithm cannot estimate NH3 absorbed on the catalyst Hence, the urea injection can be too rich or too lean. In this study, the model-based control algorithm was developed and evaluated based on the analytic model for SCR system. The channel thermo-fluid model coupled with finely tuned chemical reaction model was applied to this control algorithm. The vehicle test was carried out by using map-based and model-based control algorithms in the NEDC mode in order to evaluate the performance of the model based control algorithm.

scholarly journals Neuro-adaptive Fixed-time Non-singular Fast Terminal Sliding Mode Control Design for a Class of Under-actuated Nonlinear Systems

2021 ◽  
Author(s):  
SAFEER ULLAH ◽  
Qudrat Khan ◽  
Adeel Mehmood
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Design ◽  
Fixed Time ◽  
Control Synthesis ◽  
Terminal Sliding Mode Control ◽  
Terminal Sliding Mode ◽  
Regular Form ◽  
Fast Terminal Sliding Mode

Abstract This paper presents a fixed-time control design for a class of uncertain under-actuated nonlinear systems (UNS) using a non-singular fast terminal sliding mode control (TSMC) with a radial basis function (RBF) based estimator to achieve the fast convergence and robustness against the uncertain disturbances. The generalized mathematical model of the considered class is first reduced into an equivalent regular form, which is more convenient for any control synthesis design. A fast TSMC is designed for the transformed regular form to improve the control performance and annihilate the associated singularity problem of the conventional TSMC scheme. The steering of sliding manifold and system states in fixed-time is ensured through the Lyapunov stability theory. The RBF-based neural networks are used to adaptively estimate the nonlinear drift functions, which are feedbacked to the control input. The theoretical design, analysis and simulations of cart-pendulum and quadcopter systems demonstrate the feasibility and benefits of the regular form transformation and the designed control design. Comparing the proposed control synthesis with the standard literature presents the attractive nature of the proposed method for such a class.

Observer-Based Estimation of Aging Condition for Selective Catalytic Reduction Systems in Vehicle Applications

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Yao Ma ◽  
Junmin Wang
Keyword(s):  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Estimation Error ◽  
Nox Reduction ◽  
Observer Design ◽  
Accurate Estimation ◽  
Nox Emissions ◽  
Aging Condition ◽  
Entire Vehicle ◽  
Scr System

This paper presents two observers for estimating the aging condition of selective catalytic reduction (SCR) systems in vehicle applications. SCR systems have been widely recognized as one of the leading engine exhaust gas aftertreatment systems for reducing diesel powertrain tailpipe NOx emissions in ground vehicle applications. While fresh SCRs are quite effective in reducing tailpipe NOx emissions, their NOx reduction capabilities and performances may substantially degrade with in-service aging. To maintain the emission control performance of a SCR system for a diesel engine during the entire vehicle service life, it is thus critical to have an accurate estimation of the SCR system aging condition. In this paper, two Lyapunov-based observers utilizing the measurements of NOx and ammonia concentrations are analytically developed and verified in simulations for estimating the SCR aging condition. The measurement uncertainty is explicitly considered in the observer design process. A sufficient condition for the boundedness of the estimation error is derived. Simulation results under the US06 test cycle demonstrate the effectiveness of the proposed observers.

A Simulink Pathway for Model-Based Control of Vapor Compression Cycles

2015 ◽  
Author(s):  
Anhtuan D. Ngo ◽  
Joshua R. Cory ◽  
Brandon M. Hencey ◽  
Soumya S. Patnaik
Keyword(s):  
Control Design ◽  
Control Synthesis ◽  
Vapor Compression ◽  
Linear Quadratic ◽  
Model Based Control ◽  
Model Based ◽  
Cycle System ◽  
Vapor Compression Cycle ◽  
Compression Cycle ◽  
Transient Thermal

Current and next generation tactical aircraft face daunting thermal challenges that involve reliably maintaining thermal constraints despite large transient loads. Model-based control synthesis has the potential to improve the performance of a vapor compression cycle system during its transient operating condition, driven by intermittent and dynamic thermal loads, when compared to the current heuristic control design technique. However, the excessive labor and expertise necessary to develop models amenable to model-based control design techniques has been an impediment to widespread deployment. This paper demonstrates a Simulink pathway for model-based design via the AFRL Transient Thermal Modeling and Optimization (ATTMO) toolbox. An effective, simple linear quadratic gaussian control design is demonstrated and opens the door for widespread deployment of many advanced control techniques.

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