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Ilka, Reza, Alinejad-Beromi, Yousef. (1401). A Novel Space Reduction Technique for Design Optimization of Permanent Magnet Synchronous Motors. نشریه هنرهای کاربردی, 2(1), 1-7. doi: 10.22075/mseee.2022.25110.1082
Reza Ilka; Yousef Alinejad-Beromi. "A Novel Space Reduction Technique for Design Optimization of Permanent Magnet Synchronous Motors". نشریه هنرهای کاربردی, 2, 1, 1401, 1-7. doi: 10.22075/mseee.2022.25110.1082
Ilka, Reza, Alinejad-Beromi, Yousef. (1401). 'A Novel Space Reduction Technique for Design Optimization of Permanent Magnet Synchronous Motors', نشریه هنرهای کاربردی, 2(1), pp. 1-7. doi: 10.22075/mseee.2022.25110.1082
Ilka, Reza, Alinejad-Beromi, Yousef. A Novel Space Reduction Technique for Design Optimization of Permanent Magnet Synchronous Motors. نشریه هنرهای کاربردی, 1401; 2(1): 1-7. doi: 10.22075/mseee.2022.25110.1082

A Novel Space Reduction Technique for Design Optimization of Permanent Magnet Synchronous Motors

Modeling and Simulation in Electrical and Electronics Engineering
مقاله 1، دوره 2، شماره 1 - شماره پیاپی 7، مرداد 2022، صفحه 1-7    اصل مقاله (971.05 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/mseee.2022.25110.1082
نویسندگان
Reza Ilka1؛ Yousef Alinejad-Beromi* 2
1Researcher
2Faculty of Electrical and Computer Engineering (ECE), Semnan University,Semnan,Iran
تاریخ دریافت: 11 آبان 1400،  تاریخ بازنگری: 08 بهمن 1400،  تاریخ پذیرش: 21 شهریور 1401 
چکیده
Due to the non-linearity and large dimensions of permanent magnet motor optimization, the use of metaheuristic methods such as GA, PSO, etc. would not be the most appropriate method especially if the fitness assessment is done by a time-consuming solver such as finite element analysis (FEA). The FEA, which is widely used by most researchers, requires a lot of time and space and leads to huge computational costs. On the other hand, the accuracy of approximate analytical models is not sufficient for high-dimensional optimization tasks. To overcome these problems, a new space reduction optimization method is developed and presented in this paper. The proposed method gradually shrinks the search space and approaches an interesting subspace so that the wide variable space becomes smaller. As a result, FEA modeling accuracy is achieved as well as computational cost reductions. To validate the method, the design optimization is performed on a 2004 Toyota Prius Interior Permanent Magnet (IPM) motor. The results are compared with other optimization algorithms in terms of accuracy and number of performance evaluations. The comparison results show the superiority of the proposed algorithm, which can be a desirable alternative to industrial optimization tasks that necessarily require the least number of function evaluations.
کلیدواژه‌ها
Design Optimization؛ Space Reduction Technique؛ Problem Dependent Optimization (PDO)؛ Finite Element Analysis (FEA)؛ Interior Permanent Magnet (IPM)
مراجع
  1. Lei, J. Zhu, Y. Guo, C. Liu, and B. Ma, “A Review of Design Optimization Methods for Electrical Machines,” Energies, vol. 10, no. 12, p.1962, 2017.
  2. Duan, and D. M. Ionel, “A review of recent developments in electrical machine design optimization methods with a permanent-magnet synchronous motor benchmark study,” IEEE Transactions on Industry Applications, vol. 49, no. 3, pp.1268-1275, 2013.
  3. T. Krasopoulos, L.P. Armouti, A.G. Kladas, “Hybrid multiobjective optimization algorithm for PM motor design,” IEEE Transactions Magnetics, vol.53, no. 6, pp. 1–4, 2017.
  4. Ilka, Y. Alinejad-Beromi, and H. Yaghobi, “Techno-economic design optimization of an interior permanent-magnet synchronous motor by the multi-objective approach,” IET Electric Power Applications, vol. 12, no. 7, pp. 972-978,2018.
  5. D.S.G.Vidanalage, M. S. Toulabi, and S. Filizadeh, “Multimodal Design Optimization of V-Shaped Magnet IPM Synchronous Machines,” IEEE Transactions on Energy Conversion [Online], 2018, Available: https://ieeexplore.ieee.org/document/8294244/.
  6. S. Mirazimi, and A. Kiyoumarsi, “Magnetic Field Analysis of Multi-Flux-Barrier Interior Permanent-Magnet Motors Through Conformal Mapping,” IEEE Transactions on Magnetics, vol. 53, no. 12, pp.1-12, 2017.
  7. Ilka, Y. Alinejad-Beromi, and H. Yaghobi, “Cogging torque reduction of permanent magnet synchronous motor using multi-objective optimization,” Mathematics and Computers in Simulation, vol. 153, pp. 83-95,2018.
  8. Gao, L. Dai, and W. Zhang, “Improved genetic optimization algorithm with subdomain model for the multi-objective optimal design of SPMSM,” CES Transactions on Electrical Machines and Systems, vol. 2, no. 1, pp.160-165, 2018.
  9. Ilka, and Y. Alinejad‐Beromi, "Multiobjective optimal design of saturated surface‐mounted permanent magnet synchronous motors," International Journal of Numerical Modelling: Electronic Networks, Devices, and Fields, e2592, 2019.
  10. Liu, Q. Lin, and W. Fu, “Optimal Design of Permanent Magnet Arrangement in Synchronous Motors,” Energies, vol. 10, no. 11, pp.1700, 2017.
  11. Fodorean, L. Idoumghar, M. Brévilliers, P. Minciunescu, and C. Irimia, “Hybrid Differential Evolution Algorithm Employed for the Optimum Design of a High-Speed PMSM Used for EV Propulsion,” IEEE Transactions on Industrial Electronics, vol. 64, no. 12, pp.9824-9833, 2017.
  12. L. Jeong, and J. Hur, “Optimization Design of PMSM with Hybrid-Type Permanent Magnet Considering Irreversible Demagnetization,” IEEE Transactions on Magnetics, vol. 53, no. 11, pp.1-4, 2017.
  13. Huang, and J. Fang, “Multiphysics design and optimization of high-speed permanent-magnet electrical machines for air blower applications,” IEEE Transactions on Industrial Electronics, vol. 63, no. 5, pp.2766-2774, 2016.
  14. Wang, X. Meng, N. Guo, H. Li, J. Qiu, J. G. Zhu, Y. Guo, D. Liu, Y. Wang, and W. Xu, “Multilevel optimization for surface mounted PM machine incorporating with FEM,” IEEE Transactions on Magnetics, vol. 45, no. 10, pp.4700-4703, 2009.
  15. Lei, C. Liu, J. Zhu, and Y. Guo, “Techniques for multilevel design optimization of permanent magnet motors”, IEEE Transactions on Energy Conversion, 30(4), pp.1574-1584, 2015.
  16. W. Bandler, Q. S. Cheng, S. A. Dakroury, A. S. Mohamed, M. H. Bakr, K. Madsen, and J. Sondergaard, “Space mapping: the state of the art,” IEEE Transactions on Microwave theory and techniques, vol. 52, no. 1, pp.337-361, 2004.
  17. Crevecoeur, L. Dupré, and R. Van de Walle, “Space mapping optimization of the magnetic circuit of electrical machines including local material degradation”, IEEE transactions on magnetics, 43(6), pp.2609-2611, 2007.
  18. Gong, F. Gillon, J. T. Canh, and Y. Xu, “Proposal of a kriging output space mapping technique for electromagnetic design optimization,” IEEE Transactions on Magnetics, vol. 53, no. 6, pp.1-4, 2017.
  19. J .Y. Lee, J. H. Chang, D. H. Kang, S. I. Kim, and J. P. Hong, “Tooth shape optimization for cogging torque reduction of transverse flux rotary motor using design of experiment and response surface methodology,” IEEE Transactions on Magnetics, vol. 43, no. 4, pp.1817-1820, 2007.
  20. B. Kim, K. Y. Hwang, and B. I. Kwon, “Optimization of two-phase in-wheel IPMSM for wide speed range by using the Kriging model based on Latin hypercube sampling,” IEEE Transactions on Magnetics, vol. 47, no. 5, pp.1078-1081, 2011.
  21. A. Khan, I. Husain, M. R. Islam, and J. T. Klass, “Design of experiments to address manufacturing tolerances and process variations influencing cogging torque and back EMF in the mass production of the permanent-magnet synchronous motors”, IEEE Transactions on Industry Applications, 50(1), pp.346-355, 2014.
  22. Lee, K. Kim, S. Cho, J. Jang, T. Lee, and J. Hong, “Optimal design of interior permanent magnet synchronous motor considering the manufacturing tolerances using Taguchi robust design”, IET Electric Power Applications, 8(1), pp.23-28, 2014.
  23. C. Hwang, L. Y. Lyu, C. T. Liu, and P. L. Li, “Optimal design of an SPM motor using genetic algorithms and Taguchi method,” IEEE Transactions on Magnetics, vol. 44, no. 11, pp.4325-4328, 2008.
  24. Siklóssy, and E. Tulp, “The Space Reduction Method: A method to reduce the size of search spaces,” Information Processing Letters, vol. 38, no. 4, pp.187-192, 1991.
  25. Lei, K. R. Shao, Y. Guo, J. Zhu, and J. D. Lavers, “Sequential optimization method for the design of the electromagnetic device,” IEEE Transactions on magnetics, vol. 44, no. 11, pp.3217-3220, 2008.
  26. Lei, Y. G. Guo, J. G. Zhu, X. M. Chen, W. Xu, and K. R. Shao, “Sequential subspace optimization method for electromagnetic devices design with orthogonal design technique,” IEEE Transactions on Magnetics, vol. 48, no. 2, pp.479-482, 2012.
  27. Lebensztajn, C. A. R. Marretto, M. C. Costa, and J. L. Coulomb, “Kriging: a useful tool for electromagnetic device optimization,” IEEE Transactions on Magnetics, vol. 40, no. 2, pp.1196-1199, 2004.
  28. Lei, J. Zhu, and Y. Guo, “Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems,” Springer, New York, USA,2016.
  29. Nocedal, and S. Wright, “Numerical optimization, series in operations research and financial engineering,” Springer, New York, USA, 2006.
  30. Cavazzuti, “Optimization methods: from theory to design scientific and technological aspects in mechanics,” Springer Science & Business Media, 2012.
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