飞轮储能用径向磁悬浮轴承结构优化设计

王晓远; 张德政; 高鹏; 王谊

doi:10.13433/j.cnki.1003-8728.2018.0708

飞轮储能用径向磁悬浮轴承结构优化设计

doi: 10.13433/j.cnki.1003-8728.2018.0708

1.
天津大学电气自动化与信息工程学院, 天津 300072

详细信息

作者简介:
王晓远(1962-),教授,博士,研究方向为电机及其系统设计、电机电磁场分析,xywang62@tju.edu.cn

计量
- 文章访问数: 259
- HTML全文浏览量: 48
- PDF下载量: 15
- 被引次数: 0
出版历程
- 收稿日期: 2017-07-04
- 刊出日期: 2018-07-05

Structural Optimization Design of Radial Magnetic Bearing for Flywheel Energy Storage

1.
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

摘要

摘要: 为了提高磁轴承的承载力，同时考虑损耗、临界转速、控制刚度等问题，应对磁轴承的结构尺寸进行最优设计。本文将果蝇优化算法引进到飞轮储能用径向磁悬浮轴承的优化设计中，以尺寸参数为优化变量，以承载力、体积和轴向长度为优化目标，对径向磁悬浮轴承进行多目标优化。通过优化，径向磁悬浮轴承的承载力提高了50%，轴向长度和体积分别减小了30.6%和19.3%。结果表明，本文设计的优化算法简单有效，减小了优化工作量，具有普遍适用性。
- 径向磁悬浮轴承 /
- 承载力 /
- 果蝇优化算法 /
- 多目标优化
Abstract: In order to improve its capacity, while loss, critical speed and control stiffness are considered, the design of the structural dimensions of the radial magnetic bearing should be optimal. This paper introduces the fruit fly optimization algorithm (FOA) into the optimal design of the radial magnetic bearing(RMB) for flywheel energy storage. Its size parameter is used as an optimization variable, and its multi-objective optimization is carried out to optimize its capacity, volume and axial length. Through optimization, the carrying capacity of the RMB increases by 50%, and its axial length and volume decrease by 30.6% and 19.3% respectively. The results show that the optimization algorithm designed in this paper is simple and effective, reduces the optimization workload and has universal applicability.
- radial magnetic bearing /
- bearing capacity /
- fruit fly optimization algorithm /
- multi-objective optimization

HTML全文

参考文献(15)

[1]	Huang Z Y, Fang J C, Liu X Q, et al. Loss calculation and thermal analysis of rotors supported by active magnetic bearings for high-speed permanent-magnet electrical machines[J]. IEEE Transactions on Industrial Electronics, 2016,63(4):2027-2035
[2]	Wang H Z, Liu K, Ao P. Magnetic field and specific axial load capacity of hybrid magnetic bearing[J]. IEEE Transactions on Magnetics, 2013,49(8):4911-4917
[3]	施韦策G,布鲁勒H,特拉克斯勒A.主动磁轴承:基础、性能及应用[M].虞烈,袁崇军,译.北京:新时代出版社,1997 Schweitzer G, Bleuler H, Traxler A. Active magnetic bearing:foundation, performance and application[M]. Yu L, Yuan C J, Trans. Beijing:New Times Press, 1997(in Chinese)
[4]	Wang F X, Zhang D H, Xing J Q, et al. Study on air friction loss of high speed PM machine[C]//Proceedings of 2009 IEEE International Conference on Industrial Technology. Gippsland, Australia:IEEE, 2009:1-4
[5]	Le Y, Wang K. Design and optimization method of magnetic bearing for high-speed motor considering eddy current effects[J]. IEEE/ASME Transactions on Mechatronics, 2016,21(4):2061-2072
[6]	Lijesh K P, Hirani H. Design of eight pole radial active magnetic bearing using monotonicity[C]//Proceedings of the 9th International Conference on Industrial and Information Systems. Gwalior, India:IEEE, 2014:1-6
[7]	于宏宇. 智能优化算法的应用研究[J]. 电脑编程技巧与维护, 2012,(20):88-90 Yu H Y. The application research of intelligent optimization algorithms[J]. Computer Programming Skills and Maintenance, 2012,(20):88-90(in Chinese)
[8]	Pan W T. A new fruit fly optimization algorithm:taking the financial distress model as an example[J]. Knowledge-Based Systems, 2012,26:69-74
[9]	潘文超.果蝇最佳化演算法:最新演化式计算技术[M].台北:沧海书局,2011 Pan W C. Fruit fly optimization algorithm[M]. Taipei:Tsang Hai Publishing, 2011(in Chinese)
[10]	韩俊英,刘成忠.自适应变异的果蝇优化算法[J].计算机应用研究,2013,30(9):2641-2644 Han J Y, Liu C Z. Fruit fly optimization algorithm with adaptive mutation[J]. Application Research of Computers, 2013,30(9):2641-2644(in Chinese)
[11]	嵇尚华,张维煜,黄振跃,等.交流主动磁轴承参数设计与优化[J].中国电机工程学报,2011,31(21):150-157 Ji S H, Zhang W Y, Huang Z Y, et al. Parameter design and optimization of AC active magnetic bearing[J]. Proceedings of the CSEE, 2011,31(21):150-157(in Chinese)
[12]	Huang Z Y, Han B C. Effective approach for calculating critical speeds of high-speed permanent magnet motor rotor-shaft assemblies[J]. IET Electric Power Applications, 2015,9(9):628-633
[13]	Deng J, Wang L. A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem[J]. Swarm and Evolutionary Computation, 2017,32:121-131
[14]	Deb K. An efficient constraint handling method for genetic algorithms[J]. Computer Methods in Applied Mechanics and Engineering, 2000,186(2-4):311-338
[15]	Kim H Y, Lee C W. Analysis of eddy-current loss for design of small active magnetic bearings with solid core and rotor[J]. IEEE Transactions on Magnetics, 2004,40(5):3293-3301