Multi-objective optimization design of large-scale semi-direct drive permanent magnet wind generator

被引：1

作者：

Li, Xiangrui ^{[1
]}

Lin, Heyun ^{[1
]}

Li, Ruhai ^{[2
]}

Liu, Siqiang ^{[3
]}

Zhao, Zhen ^{[2
]}

Li, Hua ^{[2
]}

机构：

[1] School of Electrical Engineering, Southeast University, Nanjing

[2] Jiangsu CRRC Motor Co., Ltd., Yancheng

[3] CRRC Zhuzhou Electric Co., Ltd., Zhuzhou

来源：

Dianji yu Kongzhi Xuebao/Electric Machines and Control | 2024年 / 28卷 / 12期

关键词：

cost optimization; electromagnetic design; genetic algorithm; multi-objective optimization design; segmented embedded magnetic poles; semi-direct drive permanent magnet wind generator;

D O I：

10.15938/j.emc.2024.12.004

中图分类号：

学科分类号：

摘要：

Aiming at the time-consuming optimization problem based on conventional finite element method, a high-performance multi-objective optimization design method for large semi-direct-drive segmented embedded permanent magnet wind generators was proposed by combining magnetic circuit model with non-dominated genetic algorithm. This method can quickly achieve the optimal design of the motor while ensuring a certain design accuracy. First, an electromagnetic calculation model of generator was established based on equivalent magnetic circuit method, in which the field-weakening control operation can be considered. Secondly, a multi-objective optimization method for this type of generator was proposed based on the established electromagnetic model, and a non-dominated genetic algorithm was used to solve the optimization problem to obtain a design solution with high electromagnetic power and lowest material cost. Finally, the finite element analysis method was employed to verify the proposed optimal design method. The results show that the proposed method has good performance in terms of design time and optimization effect, which provides strong technical support for the optimal design of large-scale semi-direct drive permanent magnet wind generators. © 2024 Editorial Department of Electric Machines and Control. All rights reserved.

引用

页码：33 / 42

页数：9

共 26 条

[11]

GUL W, GAO Q, LENWARI W., Optimal design of a 5 MW double-stator single-rotor PMSG for offshore direct drive wind turbines, IEEE Transactions on Industry Applications, 56, 1, (2019)

[12]

LIU Yang, SONG Bao, ZHOU Xiangdong, Et al., Analysis and multi-objective optimization of spoke type vernier permanent-magnet machine [ J ], Electric Machines and Control, 27, 9, (2023)

[13]

CAO Yongjuan, GU Di, FENG Liangliang, Et al., Multi-objective preference optimization of yokeless axial-flux wind generator, Electric Machines and Control, 27, 9, (2023)

[14]

XIA Bin, WANG Chao, SUN Xin, Et al., Multi-modal optimal design of permanent magnet synchronous motor based on improved firefly algorithm, Electric Machines and Control, 28, 4, (2024)

[15]

HAO J, SUO S, YANG Y, Et al., Optimization of torque ripples in an interior permanent magnet synchronous motor based on the orthogonal experimental method and MIGA and RBF neural networks, IEEE Access, 8, (2020)

[16]

PAN Z, FANG S., Torque performance improvement of permanent magnet arc motor based on two-step strategy, IEEE Transactions on Industrial Informatics, 17, 11, (2021)

[17]

DHULIPATI H, GHOSH E, MUKUNDAN S, Et al., Advanced design optimization technique for torque profile improvement in six-phase PMSM using supervised machine learning for direct-drive EV, IEEE Transactions on Energy Conversion, 34, 4, (2019)

[18]

HUA Yizhou, LIU Yichen, PAN Wei, Et al., Multi-objective optimization design of bearingless permanent magnet synchronous motor using improved particle swarm optimization algorithm, Proceedings of CSEE, 43, 11, (2023)

[19]

XIANG Zixuan, LU Zirun, ZHU Xiaoyong, Et al., Hign-efficiency and lightweight design and optimization of spoke-type permanent magnet in-wheel motor, Proceedings of CSEE, 41, 24, (2021)

[20]

ZHENG S, ZHU X, XU L, Et al., Multi-objective optimization design of a multi-permanent-magnet motor considering magnet characteristic variation effects, IEEE Transactions on Industrial Electronics, 69, 4, (2021)

← 1 2 3 →