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

Zhiying Zhu, Jin Zhu, Hailang Zhu, Xi Zhu and Yajie Yu
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Zhiying Zhu: School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, 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

Energies, 2020, vol. 13, issue 5, 1-18

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.

Keywords: axial split-phase; bearingless flywheel machine; response surface methodology; differential evolution algorithm; parameter optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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