Model-based temperature control of a selective catalytic reduction system

Model-based temperature control of a selective catalytic reduction system

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Selective catalytic reduction (SCR) systems are commonly used for exhaust gas aftertreatment in many applications. For optimal NO x reduction using the SCR technique a certain temperature must be reached. This study deals with modelling and control of the temperature inside the SCR system for optimal catalyst operation. A first principle-based model is described for the propagation of the temperature inside the catalyst. The model is described in linear parameter varying (LPV) state-space form and used for control of the temperature using a linear-quadratic-Gaussian (LQG) controller. Necessary conditions for obtaining an optimal controller without complete state information are defined. This leads to a discrete-time LQG controller for LPV systems. The results obtained for the controller are based on several assumptions to ensure the stability of the controller. The states of the proposed model are not measurable. For this purpose, a Kalman filter-based observer is designed for estimation of the states that are used for state feedback in the controller. The observer is designed for discrete-time LPV systems and necessary assumptions for the observer are derived in the work. The resulting model of the temperature gives a model fit of up to 77% for validation data and the controller requirements are met using the proposed controller applied in a simulator environment.


    1. 1)
    2. 2)
      • 2. Westerlund, C., Westerberg, B., Odenbrand, I., Egnell, R.: ‘Model predictive control of a combined EGR/SCR HD Diesel engine’, Tech. report. SAE Technical Paper 2010-36-03-06; 2010.
    3. 3)
      • 3. Upadhyay, D., Van-Nieuwstadt, M.: ‘Modeling of a urea SCR catalyst with automotive application’. Proc. of the ASME Int. Mechanical Engineering Congress & Exposition, 2002, pp. 707713.
    4. 4)
      • 4. Ericson, C.: ‘Model Based Optimization of a Complete Diesel Engine/SCR SystemPh.D. thesis. Lund University. Lund, Sweden, 2009.
    5. 5)
    6. 6)
      • 6. Tayamon, S.: ‘Nonlinear system identification with applications to selective catalytic reduction systems’, Licentiate Thesis at Uppsala University, 2012.
    7. 7)
    8. 8)
      • 8. Rasheed, W.A., Goyal, P., Joseph, C.: ‘Model based control for a selective catalytic reduction SCR system in exhaust gas aftertreatment system for a diesel engine’. Proc. of Int. Conf. on Energy Efficient Technologies for Sustainability (ICEETS).Nagercoil – India, 2013, pp. 744749.
    9. 9)
      • 9. Sluder, C.S., Storey, J.M.E., Lewis, S.A., Lewis, L.A.: ‘Low temperature urea decomposition and SCR performance’. Tech. report. SAE Paper nr 2005-01-1858, 2005.
    10. 10)
      • 10. Schmeisser, V., Hernando, M.W.L.S., Nova, I.: ‘Cold start effect phenomena over zeolite scr catalysts for exhaust gas aftertreatment’, SAE Int. J. Commercial Veh., 2013, 6, (1), pp. 190199.
    11. 11)
      • 11. Cavina, N., Mancini, G., Corti, E., Moro, D.: ‘Thermal management strategies for SCR aftertreatment systems’. Tech. rep.. SAE Technical Paper 2013-24-0153, 2013.
    12. 12)
    13. 13)
      • 13. Steven, H.: ‘Development of a world-wide harmonised heavy-duty engine emissions test cycleTech. report. United Nations, 2001.
    14. 14)
      • 14. Tóth, R.: ‘Modeling and identification of linear parameter varying systems’ (Springer, 2010).
    15. 15)
      • 15. Mohammadpour, J., Scherer, C.W.: ‘Control of linear parameter varying systems with applications’ (Springer, 2012).
    16. 16)
      • 16. Wu, F., Packard, A.: ‘LQG control design for LPV systems’. Proc. of American Control Conf.Seattle – WA, 1995, pp. 44404444.
    17. 17)
    18. 18)
      • 18. Girard, J.W., Montreuil, C., Kim, J., Cavataio, G., Lambert, C.: ‘Technical advantages of vanadium SCR systems for diesel NOx control in emerging markets’, SAE Int. J. Fuels Lubricants, 2009, 1, (1), pp. 488494.
    19. 19)
      • 19. Nova, I., Grossale, A., Tronconi, E.: ‘Nitrates and fast SCR reaction in NOx removal from diesel engine exhausts’, Chem. Today, 2009, 27, (3), pp. 1719.
    20. 20)
    21. 21)
      • 21. Ljung, L.: ‘System identification toolbox - for use with MATLAB, User's Guide5th edn. The Mathworks, Inc.Sherborn, Mass, 2000.
    22. 22)
      • 22. Söderström, T., Stoica, P.: ‘System identification’. (Hemel Hempstead, UK, Prentice-Hall International, 1989).
    23. 23)
    24. 24)
    25. 25)
      • 25. Söderström, T.: ‘Discrete-time stochastic systems: estimation and control2nd ed. (London, U.K., Springer-Verlag, 2002).
    26. 26)
      • 26. Kalman, R.E.: ‘Mathematical description of linear dynamical systems’, SIAM Control, 1963, 1, (2), pp. 152192.
    27. 27)
      • 27. Tóth, R., Felici, F., Heuberger, P.S.C., Van den Hof, P.M.J.: ‘Discrete time LPV I/O and state space representations, differences of behavior and pitfalls of interpolation’. Proc. of the European Control Conf., 2007, pp. 54185425.
    28. 28)
      • 28. Rödönyi, G., Bokor, J., Lantos, B.: ‘LQG control of LPV systems with parameter dependent Lyapunov function’. Proc. of the 10th Mediterranean Conf., 2002.
    29. 29)
    30. 30)
      • 30. Kwakernaak, H., Sivan, R.: ‘Linear optimal control systems’ (Wiley Interscience, 1972).
    31. 31)
      • 31. Rough, W.J.: ‘Linear system theory’ (Prentice-Hall, 1996).

Related content

This is a required field
Please enter a valid email address