EN大型半直驱永磁风力发电机多目标优化设计
Multi-objective optimization design of large-scale semi-direct drive permanent magnet wind generator
- 电机与控制学报 2024年28卷第12期 页码：33-42
- 作者机构：
东南大学 电气工程学院，江苏 南京 210096
江苏中车电机有限公司，江苏 盐城 224100
中车株洲电机有限公司，湖南 株洲 412001
- 作者简介：
作者简介：李香锐（1998—），男，硕士，研究方向为半直驱永磁风力发电机电磁设计；
通信作者：林鹤云
李如海（1989—），男，博士，高级工程师，研究方向为永磁风力发电机设计；
刘斯强（1991—），男，硕士，研究方向为永磁风力发电机设计；
赵震（1983—），男，硕士，高级工程师，研究方向为永磁同步风力发电机设计；
李华（1984—），男，硕士，高级工程师，研究方向为风力发电机设计与制造。
- 基金信息：江苏省碳达峰碳中和科技创新专项资金(SBA2022080097)
DOI：10.15938/j.emc.2024.12.004
中图分类号： TM351收稿：2023-12-28，
纸质出版：2024-12
- 稿件说明：
移动端阅览
李香锐, 林鹤云, 李如海, 等. 大型半直驱永磁风力发电机多目标优化设计[J]. 电机与控制学报, 2024,28(12):33-42.
LI Xiangrui, LIN Heyun, LI Ruhai, et al. Multi-objective optimization design of large-scale semi-direct drive permanent magnet wind generator[J]. Electric Machines and Control, 2024, 28(12): 33-42.
李香锐, 林鹤云, 李如海, 等. 大型半直驱永磁风力发电机多目标优化设计[J]. 电机与控制学报, 2024,28(12):33-42. DOI： 10.15938/j.emc.2024.12.004.
LI Xiangrui, LIN Heyun, LI Ruhai, et al. Multi-objective optimization design of large-scale semi-direct drive permanent magnet wind generator[J]. Electric Machines and Control, 2024, 28(12): 33-42. DOI： 10.15938/j.emc.2024.12.004.
摘要
针对基于常规有限元法优化耗时长的问题，提出一种磁路模型与非支配遗传算法相结合的大型半直驱分段内嵌式永磁风力发电机高性能多目标优化设计方法，该方法能够在保证一定设计精度的前提下快速实现电机的优化设计。首先，基于等效磁路法建立可以考虑弱磁控制运行发电机的电磁计算模型；其次，基于所建的电磁计算模型提出了该类发电机的多目标优化方法，并采用非支配遗传算法进行求解，以获得高电磁功率和最低材料成本的设计方案；最后，采用有限元分析方法对所提出的优化设计方法进行验证。结果表明，所提方法在设计时间及寻优效果方面均具有较好的性能，可以为大型半直驱永磁风力发电机的优化设计提供有力的技术支撑。
Abstract
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 op timization effect
which provides strong technical support for the optimal design of large-scale semi-direct drive permanent magnet wind generators.
关键词
Keywords
references
王富强,郝军刚,李帅,等.漂浮式海上风电关键技术与发展趋势[J].水力发电, 2022, 48(10): 9.
WANG Fuqiang, HAO Jungang, LI Shuai, et al. Key technologies and development trends of floating offshore wind turbine[J]. Water Power, 2022, 48(10): 9.
RENATO C, FREDERIC W. Optimal design of a set of permanent magnet generators with the same cross-section[J]. Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 2013, 12(2): 678.
高剑,黄守道,张文娟,等.基于变流器控制策略的直驱永磁风力发电机优化设计[J].电工技术学报,2013,28(7):103.
GAO Jian, HUANG Shoudao, ZHANG Wenjuan, et al. Optimal design for permanent magnet wind power generator based on converter controlling algorithm[J]. Transactions of China Electrotechnical Society, 2013, 28(7): 103.
佟文明,马雪健,位海洋,等.基于磁场解析模型与遗传算法的轴向磁通永磁电机多目标优化设计[J].电机与控制学报, 2022, 26(1): 39.
TONG Wenming, MA Xuejian, WEI Haiyang, et al. Multi objective optimization design of axial flux permanent magnet motor based on magnetic field analytical model and genetic algorithm[J]. Electric Machines and Control,2022, 26(1): 39.
SHIMIZU Y, MORIMOTO S, SANADA M, et al. Automatic design system with generative adversarial network and convolutional neural network for optimization design of interior permanent magnet synchronous motor[J]. IEEE Transactions on Energy Conversion, 2021, 38(1): 724.
ISLAM M S, CHOWDHURY M, SHRESTHA A, et al. Multiload point optimization of interior permanent magnet synchronous machines for high-performance variable-speed drives[J]. IEEE Transactions on Industry Applications, 2020, 57(1): 427.
BONTHU S S R, TAREK M T B, CHOI S. Optimal torque ripple reduction technique for outer rotor permanent magnet synchronous reluctance motors[J]. IEEE Transactions on Energy Conversion, 2017, 33(3): 1184.
MIRNIKJOOS A, ABBASZADEH K, ABDOLLAHI S E. Multiobjective design optimization of a double-sided flux switching permanent magnet generator for counter-rotating wind turbine applications[J]. IEEE Transactions on Industrial Electronics,2020,68(8):6640.
MCDONALD A, BHUIYAN N A. On the optimization of generators for offshore direct drive wind turbines[J]. IEEE Transactions on Energy Conversion, 2016, 32(1): 1.
BHUIYAN N A, MCDONALD A. Optimization of offshore direct drive wind turbine generators with consideration of permanent magnet grade and temperature[J]. IEEE Transactions on Energy Conversion, 2018, 34(2): 1105.
GUL W, GAO Q, LENWARI W. Optimal design of a 5 MW double-stator single-rotor PMSG for offshore direct drive wind turbines[J]. IEEE Transactions on Industry Applications, 2019, 56(1): 216.
刘洋,宋宝,周向东,等.轮辐式游标永磁电机分析与多目标优化设计[J].电机与控制学报, 2023, 27(9): 1.
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, 2023, 27 (9): 1.
曹永娟,顾迪,冯亮亮,等.无磁轭轴向磁通风力发电机多目标偏好优化设计[J].电机与控制学报, 2023, 27 (9): 148.
CAO Yongjuan, GU Di, FENG Liangliang, et al. Multi-objective preference optimization of yokeless axial-flux wind generator[J]. Electric Machines and Control, 2023, 27(9): 148.
夏斌,王超,孙鑫,等.基于改进萤火虫算法的永磁同步电机多模态优化设计[J].电机与控制学报, 2024, 28 (4): 131.
XIA Bin, WANG Chao, SUN Xin, et al. Multi-modal optimal design of permanent magnet synchronous motor based on improved firefly algorithm[J]. Electric Machines and Control, 2024, 28 (4): 131.
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[J]. IEEE Access, 2020, 8: 27202.
PAN Z, FANG S. Torque performance improvement of permanent magnet arc motor based on two-step strategy[J]. IEEE Transac tions on Industrial Informatics, 2021, 17(11): 7523.
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 directdriveEV[J]. IEEE Transactions on Energy Conversion, 2019, 34(4): 2041.
华逸舟,刘奕辰,潘伟,等.基于改进粒子群算法的无轴承永磁同步电机多目标优化设计[J].中国电机工程学报, 2023, 43(11): 4443.
HUA Yizhou, LIU Yichen, PAN Wei, et al. Multi-objective optimization design of bearingless permanent magnet synchronous motor using improved particle swarm optimization algorithm[J]. Proceedings of CSEE, 2023, 43(11): 4443.
项子旋,卢子润,朱孝勇,等.轮辐式永磁轮毂电机高效轻质设计与优化研究[J].中国电机工程学报, 2021, 41 (24): 8283.
XIANG Zixuan, LU Zirun, ZHU Xiaoyong, et al. Hign-efficiency and lightweight design and optimization of spoke-type permanent magnet in-wheel motor[J]. Proceedings of CSEE,2021,41 (24): 8283.
ZHENG S, ZHU X, XU L, et al. Multi-objective optimization design of a multi-permanent-magnet motor considering magnet characteristic variation effects[J]. IEEE Transactions on Industrial Electronics, 2021, 69(4): 3428.
刘军伟,李华阳,钟云龙,等. 3 MW半直驱永磁风力发电机电磁设计与仿真[J].微特电机, 2020, 48(8): 27.
LIU Junwei, LI Huayang, ZHONG Yunlong, et al. Electromagnetic design and simulation of 3 MW half direct-driven permanent magnet wind power generator[J]. Small & Special Electrical Machines, 2020, 48(8): 27.
陈世坤.电机设计[M].北京:机械工业出版社, 2000.
唐任远.现代永磁电机理论与设计[M].北京:机械工业出版社, 2016.
赵震,李岩,邹强龙,等.半直驱永磁风力发电机冷却介质温度场分析研究[J].机械制造, 2018, 56(2): 30.
王秀和.永磁电机[M].北京:中国电力出版社, 2023.
DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182.
0
浏览量
859
下载量
0
CSCD
- 网络PDF下载
- Meta-XML下载
- BibTeX下载
- Endnote下载
- RefMan 下载
- NoteExpress下载
- NoteFirst下载
关联资源
相关文章
相关作者
相关机构
AI脑图
AI问答- 技术支持由北京北大方正电子有限公司提供 京ICP备09064830号-19
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies