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Modeling and control of a simplified high-speed vehicle moving in reduced-pressure conditions

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In times of rapidly progressing globalization, the possibility of fast long-distance travel between high traffic cities has become an extremely important issue. Currently, available transportation systems have numerous limitations, therefore, the idea of a high-speed transportation system moving in reduced-pressure conditions has emerged recently. This paper presents an approach to the modelling and simulation of the dynamic behaviour of a simplified high-speed vehicle that hovers over the track as a magnetically levitated system. The developed model is used for control system design. The purpose of passive and active suspension discussed in the text is to improve both the performance and stability of the vehicle as well as ride comfort of passengers travelling in a compartment. Comparative numerical studies are performed and the results of the simulations are reported in the paper with the intent to demonstrate the benefits of the approach employed here.
Rocznik
Strony
355--377
Opis fizyczny
Bibliogr. 18 poz., rys., tab., wykr.
Twórcy
  • Institute of Aeronautics and Applied Mechanics, Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, Warsaw, Poland
  • Institute of Aeronautics and Applied Mechanics, Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, Warsaw, Poland
Bibliografia
  • [1] E. Musk. Hyperloop Alpha. Technical Report. Space Exploration Technologies Corporation, 2013.
  • [2] R.F. Post and D. Ryutov. The Inductrack: a new approach to magnetic levitation. Technical Report. Lawrence Livermore National Laboratory, USA, 1996. doi: 10.2172/237425.
  • [3] A.A. Shabana, K.E. Zaazaa, and H. Sugiyama. Railroad Vehicle Dynamics: A Computational Approach. CRC Press, 2007.
  • [4] Z. Liu, Z. Long, and X. Li. Maglev Trains. Key Underlying Technologies. Part of the Springer Tracts in Mechanical Engineering book series, Springer, 2015. doi: 10.1007/978-3-662-45673-6_1.
  • [5] Y. Cai, S.S. Chen, and D.M. Rote. Dynamics and controls in maglev systems. Technical Report, Argonne National Laboratory, USA, 1992. doi: 10.2172/10136539.
  • [6] P.K. Sinha. Electromagnetic Suspension Dynamics and Control. Peter Peregrinus Ltd., London, UK, 1987.
  • [7] M. Appleyard and P.E. Wellstead. Active suspensions: some background. IEE Proceedings – Control Theory and Applications, 142(2):123–128, 1995. doi: 10.1049/ip-cta:19951735.
  • [8] K.D. Rao. Modeling, simulation and control of semi active suspension system for automobiles under MATLAB Simulink using PID controller. IFAC Proceedings Volumes, 47(1):827–831, 2014. doi: 10.3182/20140313-3-IN-3024.00094.
  • [9] D. Hanafi. PID controller design for semi-active car suspension based on model from intelligent system identification. In: 2010 Second International Conference on Computer Engineering and Applications, volume 2, pages 60–63, Bali Island, Indonesia, 19-21 March 2010. doi: 10.1109/ICCEA.2010.168.
  • [10] M. Sentil Kumar. Development of active suspension system for automobiles using PID controller. Proceedings of the World Congress on Engineering 2008, volume II, pages 1472–1477, London, UK, 2-4 July, 2008.
  • [11] A.J. Truscott and P.E. Wellstead. Adaptive ride control in active suspension systems. Vehicle System Dynamics, 24(3):197–230, 1995. doi: 10.1080/00423119508969088.
  • [12] U.N.L.T. Alves, J.P.F. Garcia, M.C.M. Teixeira, S.C. Garcia, and F.B. Rodrigues. Sliding mode control for active suspension system with data acquisition delay. Mathematical Problems in Engineering 2014:1-13, 2014. doi: 10.1155/2014/529293.
  • [13] Y. Cai, S.S. Chen, T.M. Mulcahy, and D.M. Rote. Dynamic stability of maglev systems. Technical Report, Argonne National Laboratory, USA, 1992. doi: 10.2172/10110331.
  • [14] R.M. Katz, V.D. Nene,R.J. Ravera, and C.A. Skalski. Performance of magnetic suspensions for high speed vehicles operating over flexible guideways. Journal of Dynamic Systems, Measurement, and Control, 96(2):204–212. doi: 10.1115/1.3426792.
  • [15] W. Kortüm, W. Schwartz, and I. Fayé. Dynamic modeling of high speed ground transportation vehicles for control design and performance evaluation. In: Schweitzer G., Mansour M. (eds.), Dynamics of Controlled Mechanical Systems. Proceedings of IUTAM/IFAC Symposium, pages 335–350, Zurich, Switzerland, May 30–June 3, 1988. doi: 10.1007/978-3-642-83581-0_26.
  • [16] K.J. Aström and R.M. Murray. Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, USA, 2008.
  • [17] P. Maciąg, P. Malczyk, and J. Frączek. Optimal design of multibody systems using the adjoint method. In: Awrejcewicz J. (ed.), Dynamical Systems in Applications, pages 240–253. Springer, 2018. doi: 10.1007/978-3-319-96601-4_22.
  • [18] Y. Zhu, C. Sandu, D. Dopico, and A. Sandu. Benchmarking of adjoint sensitivity-based optimization techniques using a vehicle ride case study. Mechanics Based Design of Structures and Machines, 46(2):254–266, 2018. doi: 10.1080/15397734.2017.1338576.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a856b9db-8656-49c0-8000-b48858419b1e
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