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Optimization Design of an Axial Split-Phase Bearingless Flywheel Machine with Magnetic Sleeve and Pole-Shoe Tooth by RSM and DE Algorithm

Author

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  • Zhiying Zhu

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
    School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Jin Zhu

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

  • Hailang Zhu

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

  • Xi Zhu

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

  • Yajie Yu

    (School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

Abstract

In order to improve the suspension and torque performance of a bearingless flywheel machine, a new type of axial split-phase bearingless flywheel machine with a magnetic sleeve and pole-shoe tooth is analyzed and optimized as described in this paper. Based on the basic structure and working characteristics of the machine, the response surface methodology (RSM) and differential evolution (DE) algorithm are adopted to further optimize the parameters of the stator teeth of the machine to improve the radial space utilization and motor output performance. Firstly, the Box–Behnken design (BBD) and finite element analysis (FEA) are combined to select the representative optimization parameter combinations to establish the sample data space, and the response surface models of machine torque and suspension force are established using the least square method. Besides this, the DE algorithm is employed to obtain the optimal tooth profile parameter configuration for the multi-objective optimization of machine performance. Finally, the output performances of the machine before and after optimization are compared under initial and optimized winding turns. The results show that, compared with the initial structure, the average torque and suspension force of the optimized machine increase by 36.46 % and 108.22% respectively, which demonstrates the effectiveness of the tooth profile optimization method. At the same time, an experimental prototype is also produced, laying the experimental foundation for further practical exploration.

Suggested Citation

  • Zhiying Zhu & Jin Zhu & Hailang Zhu & Xi Zhu & Yajie Yu, 2020. "Optimization Design of an Axial Split-Phase Bearingless Flywheel Machine with Magnetic Sleeve and Pole-Shoe Tooth by RSM and DE Algorithm," Energies, MDPI, vol. 13(5), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1256-:d:330014
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    References listed on IDEAS

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    1. Mousavi G, S.M. & Faraji, Faramarz & Majazi, Abbas & Al-Haddad, Kamal, 2017. "A comprehensive review of Flywheel Energy Storage System technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 477-490.
    2. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
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    Cited by:

    1. Roberto Rocca & Savvas Papadopoulos & Mohamed Rashed & George Prassinos & Fabio Giulii Capponi & Michael Galea, 2020. "Design Trade-Offs and Feasibility Assessment of a Novel One-Body, Laminated-Rotor Flywheel Switched Reluctance Machine," Energies, MDPI, vol. 13(22), pages 1-19, November.
    2. Aswin Balasubramanian & Floran Martin & Md Masum Billah & Osaruyi Osemwinyen & Anouar Belahcen, 2021. "Application of Surrogate Optimization Routine with Clustering Technique for Optimal Design of an Induction Motor," Energies, MDPI, vol. 14(16), pages 1-19, August.

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