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International journal of automotive technology v.10 no.6, 2009년, pp.653 - 662   피인용횟수: 1

MODEL-BASED CONTROL SYSTEM DESIGN IN A UREA-SCR AFTERTREATMENT SYSTEM BASED ON $NH_3$ SENSOR FEEDBACK

Devarakonda, M.    (ME-EM Department, Michigan Technological University   ); Parker, G.    (ME-EM Department, Michigan Technological University   ); Johnson, J.H.    (ME-EM Department, Michigan Technological University   ); Strots, V.    (Advanced Aftertreatment Technologies, Navistar Inc  );
  • 초록

    This paper presents preliminary control system simulation results in a urea-selective catalytic reduction (SCR) aftertreatment system based on $NH_3$ sensor feedback. A four-state control-oriented lumped parameter model is used to analyze the controllability and observability properties of the urea-SCR plant. A model-based estimator is designed via simulation and a control system is developed with design based on a sliding mode control framework. The control system based on $NH_3$ sensor feedback is analyzed via simulation by comparing it to a control system developed based on $NO_x$ sensor feedback. Simulation results show that the $NH_3$ sensor-based strategy performs very similarly in comparison to a $NO_x$ sensor-based strategy. The control system performance metrics for $NO_x$ index, urea index, urea usage, and $NH_3$ slip suggest that the $NO_x$ sensor can be a potential alternative to a $NO_x$ sensor for urea-SCR control applications.


  • 주제어

    Urea-SCR catalyst .   Model-based estimation .   Observer .   Control system design .   $NH_3$ sensor .   Sliding mode control.  

  • 참고문헌 (16)

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    3. Devarakonda, M., Parker, G., Johnson, J. H., Strots, V. and Santhanam, S. (2008b). Model based estimation and control strategy development for urea-SCR aftertreatment system. Int. J. Fuels and Lubricants 1, 1, 646?661 
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    6. Devarakonda, M. N., (2008c). Dynamic Modeling, Simulation and Development of Model Based Control Strategies in a Urea-SCR Aftertreatment System for Heavy Duty Diesel Engines. Ph.D. Dissertation. Michigan Tech University 
    7. Upadhyay, D. and Van Nieuwstadt, M. (2006). Model based analysis and control design of a Urea-SCR DeNOx aftertreatment system. ASME J. Dynamic Systems, Measurement and Control, 128 
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    9. Krocher, O., Devadas, M., Elsener, M., Wokaun, A., Soger, N., Pfeifer, M., Demel, Y. and Mussmann, L. (2006). Investigation of the selective catalytic reduction of NO by NH3 on Fe-ZSM5 monolith catalysts. Applied Catalysis B: Environmental, 66, 208?216 
    10. Devarakonda, M., Parker, G., Johnson, J. H., Strots, V. and Santhanam, S. (2008a). Adequacy of reduced order models for model based control in a urea-SCR aftertreatment system. SAE Paper No. 2008-01-0617 (Also accepted as a special publication in SP-2155) 
    11. Wingbrant, H., Svenningstorp, H., Salomonsson, P., Kubinski, D., Visser, J., Lofdahl, M. and Spetz, A. (2005). Using a MISic-FET sensor for detecting NH3 in SCR systems. IEEE Sensors J., 5, 1099?1105 
    12. Tronconi, E., Nova, I., Grossale, A. and Ciardelli, C. (2007). Catalytic mechanism, detailed kinetics and converter model for NH3-SCR of NOx emissions from vehicles. Cross-cut Lean Exhaust Emissions Reduction Simulation (CLEERS) Workshop. www.cleers.org 
    13. Upadhyay, D. and Van Nieuwstadt (2002). Control design of an automotive urea SCR catalyst. ASME Int. Mechanical Engineering Cong. and Exposition, IMECE2002-32103 
    14. Wang, D., Tao, S., Cabush, D. and Racine, D. (2007). Ammonia sensor for SCR NOx reduction. Diesel Engines Emissions Reduction (DEER) Conf 
    15. Devarakonda, M., Parker, G., Johnson, J. H. and Strots, V. (2008d). Simulation based control system analysis of a urea SCR aftertreatment system based on NH$_{3}$ sensor feedback. Cross-cut Lean Exhaust Emissions Reduction Simullation (CLEERS) Workshop. www.cleers.org 
    16. Devadas, M., Krocher, O. and Wokaun, A. (2005). Catalytic investigation of Fe-ZSM5 in the selective catalytic reduction of NOx with NH$_{3}$. Reaction Kinetics and Catalysis Letters, 86, 347?354 
  • 이 논문을 인용한 문헌 (1)

    1. 2015. "" Environmental engineering research, 20(2): 155~161     

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