PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Geometrical sensitivity analysis based on design optimization and multiphysics analysis of PM assisted synchronous reluctance motor

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Anisotropic rotor configurations influenced by the presence of a large number of geometrical parameters in a permanent magnet assisted synchronous reluctance (PMASR) motor pose design challenges in obtaining a robust geometry satisfying the requirements of reduced torque ripple and high torque density. Therefore, the purpose of this work is to perform detailed geometrical sensitivity analysis of a 36 slot/4 pole permanent magnet assisted synchronous reluctance (PMASR) motor using h-indexing and level sensitivity analysis in order to specify a guideline for designers to prioritize the design variables for optimization. Systematic multi-level design optimization for multiple objectives is implemented by an NSGA-II algorithm aided by the finite element analysis tool, hardware prototyping and experimental validation. The optimized designs also exhibit better structural and thermal characteristics.
Rocznik
Strony
155--163
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wykr.
Twórcy
  • Electrical and Electronics Engineering, SSN College of Engineering, Old Mahabalipuram Road, Kalavakkam, Tamil Nadu 603110, India
autor
  • Electrical and Electronics Engineering, SSN College of Engineering, Old Mahabalipuram Road, Kalavakkam, Tamil Nadu 603110, India
  • Electrical and Electronics Engineering, SSN College of Engineering, Old Mahabalipuram Road, Kalavakkam, Tamil Nadu 603110, India
Bibliografia
  • [1] D.H. Jung, Y. Kwak, J. Lee, and C.S. Jin, “Study on the optimal design of PMa-SynRM loading ratio for achievement of ultrapremium efficiency”, IEEE Trans. Magn. 53 (6), 1‒4 (2017).
  • [2] S. Morimoto, S. Ooi, Y. Inoue, and M. Sanada, “Experimental evaluation of a rare-earth-free PMASynRM with ferrite magnets for automotive applications”, IEEE Trans. Ind. Elec. 61 (10), 5749‒5756 (2014).
  • [3] H. Cai, B. Guan, and L. Xu, “Low-cost ferrite PM-assisted synchronous reluctance machine for electric vehicles”, IEEE Trans. Ind. Elec. 61 (10), 5741‒5748 (2014).
  • [4] K. Wang, Z.Q. Zhu, G. Ombach, M. Koch, S. Zhang, and J. Xu, “Torque ripple reduction of synchronous reluctance machines optimal slot/pole and flux-barrier layer number combinations”, COMPEL – The international journal for computation and mathematics in electrical and electronic engineering 34 (1), 3–17 (2015).
  • [5] M. Gamba, G. Pellegrino, and F. Cupertino, “Optimal number of rotor parameters for the automatic design of synchronous reluctance machines”, Int. Conf. Electrical Machines ICEM 1334‒1340 (2014).
  • [6] N. Bianchi, M. Degano, and E. Fornasiero, “Sensitivity analysis of torque ripple reduction of synchronous reluctance and interior PM motors”, IEEE Trans. Ind. Appl. 51 (1), 187‒195 (2015).
  • [7] V.S. Nagarajan, M. Balaji, V. Kamaraj, R. Arumugam, N. Ganesh, S. Srivignesh, and M. Suudharshana, “Design optimization of ferrite assisted synchronous reluctance motor using multi-objective differential evolution algorithm”, COMPEL – The international journal for computation and mathematics in electrical and electronic engineering 36 (1), 219–239 (2017).
  • [8] V.S. Nagarajan, V. Kamaraj, M. Balaji, R. Arumugam, N. Ganesh, R. Rahul, and M. Lohit, “Effect of geometrical parameters on optimal design of synchronous reluctance motor”, J. Magn. 21 (4), 544‒553 (2016).
  • [9] X. Zhu, Z. Shu, L. Quan, Z. Xiang, and X. Pan, “Multi-objective optimization of an outer-rotor v-shaped permanent magnet flux switching motor based on multi-level design method”, IEEE Trans. Magn. 52 (10), 1‒8 (2016).
  • [10] Z. Xiang, X. Zhu, L. Quan, Y. Du, C. Zhang, and D. Fan, “Multilevel design optimization and operation of a brushless double mechanical port flux-switching permanent-magnet motor”, IEEE Trans. Ind. Elec. 63 (10), 6042‒6054 (2016).
  • [11] J.K. Sykulski, “Computational electromagnetics for design optimisation: the state of the art and conjectures for the future”, Bull. Pol. Ac.: Tech. 57 (2), 123–131 (2009).
  • [12] P. Kedzierski, A. Morka, G. Slawinski, and T. Niezgoda, “Optimization of two-component armour”, Bull. Pol. Ac.: Tech. 63 (1), 173–179 (2015).
  • [13] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II”, IEEE Trans. Evol. Comp. 6 (2), 182‒197 (2002).
  • [14] Dlugosz and T. Burczynski, “Multiobjective shape optimization of selected coupled problems by means of evolutionary algorithms”, Bull. Pol. Ac.: Tech. 60 (2), 215–222 (2012).
  • [15] S. Berhausen and S. Paszek, “Use of the finite element method for parameter estimation of the circuit model of a high power synchronous generator”, Bull. Pol. Ac.: Tech. 63 (3), 575–582 (2015).
  • [16] Lebkowski, “A way of neodymium-iron-boron magnets regeneration in surface-mounted PMSM used in electric vehicles”, Bull. Pol. Ac.: Tech. 65 (5), 751–758 (2017).
  • [17] Y. Wang, D.M. Ionel, M. Jiang, and S.J. Stretz, “Establishing the relative merits of synchronous reluctance and PM assisted technology through systematic design optimization,” IEEE Trans. Ind. Appl. 52 (4), 2971‒2978 (2016).
  • [18] A. Fatemi, N.A. O. Demerdash, T.W. Nehl, and D.M. Ionel, “Large-scale design optimization of PM machines over a target operating cycle”, IEEE Trans. Ind. Appl. 52 (5), 3772‒3782 (2016).
  • [19] W. Zhao, F. Xing, X. Wang, T.A. Lipo, and B.I. Kwon, “Design and analysis of a novel PM-assisted synchronous reluctance machine with axially integrated magnets by the finite-element method”, IEEE Trans. Magn. 53 (6), 1‒4 (2017).
  • [20] M. Nowak, “Improved aeroelastic design through structural optimization”, Bull. Pol. Ac.: Tech. 60 (2), 237–240 (2012).
  • [21] W. Ostapski, A. Arominski, and S. Dowkontt, “The vibration of prototype aircraft propeller speed reduction unit – test bench and FEM numerical simulation study”,Bull. Pol. Ac.: Tech. 62 (4), 861–873 (2014).
  • [22] MagNet and MotorSolve, Infolytica, http://www.infolytica.com/.
  • [23] G. Extremiana, G. Abad, J. Arza, J. Chivite-Zabalza, and I. Torre, “Rotor flux oriented control of induction machine based drives with compensation for the variation of all machine parameters”, Bull. Pol. Ac.: Tech. 61 (2), 309–324 (2013).
  • [24] P. Brown, “Measure theory and the central limit theorem”, VIGRE REU (2011).
  • [25] Z.R. Smith and C.S. Wells, “Central limit theorem and sample size”, Annual meeting of the Northeastern Educational Research Association NERA (2006).
  • [26] MATLAB, MathWorks, https://www.mathworks.com/products/matlab.html.
  • [27] ANSYS Multiphysics, www.ansys.com/en-in/products/platform/multiphysics-simulation.
Uwagi
EN
This research was supported and funded by the Department of Science and Technology, the Government of India and the SSN Trust.
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-662f27cc-0158-4dd1-af10-3ce182c23cf8
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.