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Multi-objective Optimization Method for Permanent Magnet-assisted Synchronous Reluctance Motor Based on KELM-NSGA-II
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Chao-zhi HUANG, Si-ying LI, Xiao-bo LIU, Yan-wen SUN
Science Technology and Engineering | 2025, 25(3) : 1065 - 1074
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Science Technology and Engineering | 2025, 25(3): 1065-1074
Papers·Electrical Technology
Multi-objective Optimization Method for Permanent Magnet-assisted Synchronous Reluctance Motor Based on KELM-NSGA-II
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Chao-zhi HUANG, Si-ying LI, Xiao-bo LIU, Yan-wen SUN
Affiliations
  • School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China
Published: 2025-01-28 doi: 10.12404/j.issn.1671-1815.2402538
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In order to improve the output performance of permanent magnet assisted synchronous reluctance motor (PMa-SynRM), a multi-objective optimization design method for external rotor PMa-SynRM based on kernel extreme learning machine (KELM) and fast non-dominated sorting genetic algorithm (NSGA-II) was proposed. Firstly, the preliminary design of the PMa-SynRM rotor magnetic barrier was carried out and the working principle of the PMa-SynRM was analyzed. Secondly, the influence of each design variable on the optimization goal was evaluated through comprehensive sensitivity analysis, and the main optimization parameters were selected. Thirdly, with high output torque, high efficiency and low torque ripple as the optimization goals, a surrogate model based on KELM was established. Finally, NSGA-II was used for global optimization, and the optimal solution was selected from the Pareto frontier generated by NSGA-II, which was verified by finite element analysis. The simulation results show that the average torque of the optimized motor is increased by 15.83%, the torque ripple is reduced by 60.27%, and the efficiency of the optimized motor is also improved compared with the initial motor, which verifies the effectiveness of the optimized design method proposed in this paper.

permanent magnet-assisted synchronous reluctance motor  /  KELM  /  multi-objective optimization  /  NSGA-II
Chao-zhi HUANG, Si-ying LI, Xiao-bo LIU, Yan-wen SUN. Multi-objective Optimization Method for Permanent Magnet-assisted Synchronous Reluctance Motor Based on KELM-NSGA-II[J]. Science Technology and Engineering, 2025 , 25 (3) : 1065 -1074 . DOI: 10.12404/j.issn.1671-1815.2402538
Year 2025 volume 25 Issue 3
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doi: 10.12404/j.issn.1671-1815.2402538
  • Receive Date:2024-04-09
  • Online Date:2025-07-29
  • Published:2025-01-28
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  • Received:2024-04-09
  • Revised:2024-07-18
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    School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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