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Introduction to the benchmark challenge on common rail pressure control of gasoline direct injection engines

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Abstract

As one of the most important actuators for gasoline direct injection technology, common rail systems provide the requested rail pressure for fuel injection. Special system characteristics, such as coupled discrete-continuous dynamic in the common rail system, limited measurable states, and time-varying engine operating conditions, impel the combination of advanced methods to obtain the desired injection pressure. Therefore, reducing the pressure fluctuation and satisfying engineering implementation have become noteworthy issues for rail pressure control (RPC) systems. In this study, the benchmark problem and the design specification of RPC proposed by 2018 IFAC E-CoSM Committee are introduced. Moreover, a common rail system model is provided to the challengers, and a traditional PI control is applied to show the problem behaviors. Finally, intermediate results of the challengers are summarized briefly.

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References

  1. M. Fry, J. King, C. White. A comparison of gasoline direct injection systems and discussion of development techniques. International Congress & Exposition, Detroit, 1999: DOI https://doi.org/10.4271/1999-01-0171.

    Google Scholar 

  2. E. Achleitner, H. Bäcker, A. Funaioli. Direct injection systems for Otto engines. SAE World Congress & Exhibition, Detroit, 2007: DOI https://doi.org/10.4271/2007-01-1416.

    Google Scholar 

  3. C. L. Wei, X. X. Guo, Z. P. Feng, et al. Current application situations and development trend of gasoline direct injection engine. Small Internal Combustion Engine & Vehicle Technique, 2014, 43(5): 78–81.

    Google Scholar 

  4. Z. H. Feng, C. Zhan, C. L. Tang, et al. Experimental investigation on spray and atomization characteristics of diesel gasoline ethanol blends in high pressure common rail injection system. Energy, 2016, 112: 549–561.

    Article  Google Scholar 

  5. C. L. Myung, S. Park. Exhaust nanoparticle emissions from internal combustion engines: a review. International Journal of Automotive Technology, 2012, 13(1): 9–22.

    Article  Google Scholar 

  6. H. F. Su, Y. T. Zhang, J. Wang, et al. Researches of commonrail diesel engine emission control based on cylinder pressure feedback. Proceedings of the IEEE Vehicle Power and Propulsion Conference, Harbin: IEEE, 2008: 1–6.

    Google Scholar 

  7. N. Giorgetti, G. Ripaccioli, A. Bemporad, et al. Hybrid model predictive control of direct injection stratified charge engines. IEEE/ASME Transactions Mechatronics, 2006, 11(5): 499–506.

    Article  Google Scholar 

  8. H. J. Tang, L. Weng, Z. Y. Dong, et al. Adaptive and learning control for SI engine model with uncertainties. IEEE/ASME Transactions on Mechatronics, 2009, 14(1): 93–104.

    Article  Google Scholar 

  9. F. Yan, J. Wang. Common rail injection system iterative learning control based parameter calibration for accurate fuel injection quantity control. International Journal of Automotive Technology, 2011, 12(2): 149–157.

    Article  Google Scholar 

  10. R. Baur. J. Blath, C. Bohn, et al. Modeling and identification of a gasoline common rail injection system. SAE Technical Paper 2014-01–0196, 2014: DOI https://doi.org/10.4271/2014-01-0196.

    Google Scholar 

  11. A. de Risi, F. Naccarato, D. Laforgia. Experimental analysis of common rail pressure wave effect on engine emissions. SAE World Congress & Exhibition, Detroit, 2005: DOI https://doi.org/10.4271/2005-01-0373.

    Google Scholar 

  12. A. Ferrari, P. Pizzo. Fully predictive common rail fuel injection apparatus model and its application to global system dynamics analyses. International Journal of Engine Research, 2017, 18(3): 273–290.

    Article  Google Scholar 

  13. L. Postrioti, A. Cavicchi, D. Paolino, et al. An experimental and numerical analysis of pressure pulsation effects of a gasoline direct injection system. Fuel, 2016, 173: 8–28.

    Article  Google Scholar 

  14. J. Lee, H. Liu, Y. Noh, et al. A model based design analysis for a gasoline direct injection pump. SAE World Congress & Exhibition, Detroit, 2015: DOI https://doi.org/10.4271/2015-01-1267.

    Google Scholar 

  15. M. Corno, F. Casella, S M. Savaresi, et al. Object-oriented modelling of a gasoline direct injection system. Proceedings of the 6th International Modelica Conference, Modelica, 2008: 83–91.

    Google Scholar 

  16. A. de Gaeta, G. Fiengo, A. Palladino, et al. Control oriented model of a common-rail system for gasoline direct injection engine. Proceedings of the 28th Chinese Control Conference, Shanghai: IEEE, 2009: 6614–6619.

    Google Scholar 

  17. A. de Gaeta, G. Fiengo, A. Palladino, et al. Design and experimental validation of a model-based injection pressure controller in a common rail system for GDI engine. Proceedings of the American Control Conference, San Francisco: IEEE, 2011: 5273–5278.

    Google Scholar 

  18. A. Balluchi, A. Bicchi, E. Mazzi, et al. Hybrid modelling and control of the common rail injection system. Hybrid Systems: Computation and Control, Santa Barbara: Springer, 2006: 79–92.

    Chapter  Google Scholar 

  19. U. Montanaro, A. de Gaeta, V. Giglio. An MRAC approach for tracking and ripple attenuation of the common rail pressure for GDI engines. Proceedings of the 18th IFAC World Congress, Milano, Italy, 2011: 4173–4180.

    Google Scholar 

  20. P. Lino, B. Maione, A. Rizzo. A control-oriented model of a common rail injection system for diesel engines.Proceedings of the 10th IEEE Conference on Emerging Technologies, Catania, Italy, 2005: 557–563.

    Google Scholar 

  21. P. Lino, B. Maione, A. Rizzo. Nonlinear modelling and control of a common rail injection system for diesel engines. Applied Mathematical Modelling, 2007, 31(9): 1770–1784.

    Article  Google Scholar 

  22. H. Chen, X. Gong, Q. F. Liu, et al. Triple-step method to design nonlinear controller for rail pressure of gasoline direct injection engines. IET Control Theory & Applications, 2014, 8(11): 948–959.

    Article  Google Scholar 

  23. Q. F. Liu, X. Gong, H. Chen, et al. Nonlinear GDI rail pressure control: design, analysis and experimental implementation. Proceedings of the 34th Chinese Control Conference, Hangzhou: IEEE, 2015: 8132–8139.

    Google Scholar 

  24. Q. F. Liu, H. Chen, Y. F. Hu, et al. Modeling and control of the fuel injection system for rail pressure regulation in GDI engine. IEEE/ASME Transactions on Mechatronics, 2014, 19(3): 1501–1513.

    Google Scholar 

  25. Q. F. Liu. Research on Nonlinear Control and Its Application in Vehicle Powertrain Systems. Changchun: Jilin University, 2014.

    Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Automotive Simulation and Control, Changchun Jilin, 130025, China

    Qifang Liu, Jinlong Hong, Bingzhao Gao & Hong Chen

  2. Department of Control Science and Engineering, Jilin University, Changchun Jilin, 130025, China

    Qifang Liu & Hong Chen

Authors
  1. Qifang Liu
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  2. Jinlong Hong
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  3. Bingzhao Gao
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  4. Hong Chen
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Corresponding author

Correspondence to Hong Chen.

Additional information

This work was supported by the National Nature Science Foundation of China (Nos. 61790564, 61803173) and the Program for Natural Science Foundation of Jilin Province (No. 20190103047JH).

Qifang LIU received the B.Sc. and Ph.D. degrees in Control Theory and Engineering from Jilin University, Changchun, China, in 2009 and 2014, respectively. She is currently a Lecturer with Jilin University. Her current research interest includes vehicle powertrain control.

Jinlong HONG received his B.Sc. degree from the Yanshan University, China, in 2014. He is currently a Ph.D. candidate in the Jilin University and his main research is drivability control of AMT vehicles.

Bingzhao GAO received his B.Sc. degree from the Jilin University of Technology, China, in 1998, M.Sc. degree and Ph.D. in Control Engineering from the Jilin University, China, in 2002 and 2009, respectively, and Ph.D. in Mechanical Engineering from the Yokohama National University, Japan. He is currently a Professor at the Jilin University. His research interests include vehicle powertrain control and vehicle stability control.

Hong CHEN received the B.Sc. and M.Sc. degrees in Process Control from Zhejiang University, Zhejiang, China, in 1983 and 1986, respectively, and the Ph.D. degree in System Dynamics and Control Engineering from the University of Stuttgart, Stuttgart, Germany, in 1997. Since 1999, she has been a Professor with Jilin University, Changchun, China, where she currently serves as a Tang Aoqing Professor and the Director of the State Key Laboratory of Automotive Simulation and Control. Her current research interests include model predictive control, optimal and robust control, and nonlinear control and applications in mechatronic systems focusing on automotive systems.

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Liu, Q., Hong, J., Gao, B. et al. Introduction to the benchmark challenge on common rail pressure control of gasoline direct injection engines. Control Theory Technol. 17, 167–175 (2019). https://doi.org/10.1007/s11768-019-8258-7

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  • DOI: https://doi.org/10.1007/s11768-019-8258-7

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