新型盘式横向磁通永磁无刷电机的结构原理及设计优化

doi:10.19595/j.cnki.1000-6753.tces.200401

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Abstract As the executive device of industrial robots, servo motors generally adopt surface- mounted permanent magnet synchronous motors. However, the axial winding ends and higher-quality rotors of this type of motor cannot satisfy the requirements of miniaturization and high dynamics. In this paper, a novel disk-type transverse flux permanent magnet brushless motor (DTFM) applied to industrial robots is proposed. By eliminating the axial winding ends and designing inner space reasonably combined with the specific requirements of industrial robots, the volume of the motor can be effectively reduced. In addition, small volume and low-quality disk structure enhances the dynamic performance of the motor. First, the structure and principle of DTFM are introduced. Then, the power equation and the main dimensions of DTFM are deduced, and a set of preliminary design schemes are obtained. Furthermore, the influence of structure parameters on performance is analyzed, and a new multi-objective optimization strategy combining neural network and multi-objective particle swarm algorithm is used to optimize the DTFM. Finally, a prototype DTFM is manufactured and the superiority of the DTFM is verified through experiment.

Key words： Industrial robots transverse flux motor disk motor soft magnetic composite material multi-objective optimization

Received: 21 April 2020

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TM351

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	Zhang Wenjing
	Xu Yanliang
	Li Shucai

Cite this article:

Zhang Wenjing,Xu Yanliang,Li Shucai. Structure Principle and Optimization of a Novel Disk Transverse Flux Permanent Magnet Brushless Motor[J]. Transactions of China Electrotechnical Society, 2021, 36(14): 2979-2988.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.200401 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I14/2979

[1] 孙维, 张咏行, 赵永杰, 等. 重载工业机器人研究现状[J]. 汕头大学学报: 自然科学版, 2020, 35(1): 3-15, 2.
Sun Wei, Zhang Yongxing, Zhao Yongjie, et al.Research status of heavy-duty industrial robots[J]. Journal of Shantou University: Natural Science Edition, 2020, 35(1): 3-15, 2.
[2] 王田苗, 陶永. 我国工业机器人技术现状与产业化发展战略[J]. 机械工程学报, 2014, 50(9): 1-13.
Wang Tianmiao, Tao Yong.Research status and industrialization development strategy of Chinese industrial robot[J]. Journal of Mechanical Engin- eering, 2014, 50(9): 1-13.
[3] 黄宣睿, 宋宇洋, 李秋生, 等. 一种基于内模控制的工业机器人关节伺服系统振动抑制算法[J]. 电工技术学报, 2019, 34(3): 497-505.
Huang Xuanrui, Song Yuyang, Li Qiusheng, et al.A vibration suppression algorithm for industrial robot joint servo system based on internal model control[J]. Transactions of China Electrotechnical Society, 2019, 34(3): 497-505.
[4] 左月飞, 张捷, 刘闯, 等. 基于自抗扰控制的永磁同步电机位置伺服系统一体化设计[J]. 电工技术学报, 2016, 31(11): 51-58.
Zuo Yuefei, Zhang Jie, Liu Chuang, et al.Integrated design for permanent magnet synchronous motor servo systems based on active disturbance rejection control[J]. Transactions of China Electrotechnical Society, 2016, 31(11): 51-58.
[5] Staszak J, Ludwinek K, Gawecki Z, et al.Utilization of permanent magnet synchronous motors in industrial robots[C]//2015 International Conference on Information and Digital Technologies, Zilina, Slovakia, 2015: 342-347.
[6] 王恩德, 黄声华. 表贴式永磁同步电机伺服系统电流环设计[J]. 中国电机工程学报, 2012, 32(33): 82-88, 179.
Wang Ende, Huang Shenghua.Current regulator design for surface permanent magnet synchronous motor servo systems[J]. Proceedings of the CSEE, 2012, 32(33): 82-88, 179.
[7] Ando S, Goto T. Current status and future of intelligent industrial robots[J]. IEEE Transactions on Industrial Electronics, 1983, IE-30(3): 291-299.
[8] Hsu Y S, Tsai M C.Development of a novel transverse flux wheel motor[J]. IEEE Transactions on Magnetics, 2011, 47(10): 3677-3680.
[9] Yang Guolong, Cheng Dansong, Zhang He, et al.Bidirectional cross-linking transverse flux permanent magnet synchronous motor[J]. IEEE Transactions on Magnetics, 2013, 49(3): 1242-1248.
[10] Doering J, Steinborn G, Hofmann W.Torque, power, losses, and heat calculation of a transverse flux reluctance machine with soft magnetic composite materials and disk-shaped rotor[J]. IEEE Transa- ctions on Industry Applications, 2015, 51(2): 1494-1504.
[11] 徐衍亮, 吴巧变, 宫晓. 新型盘式横向磁通永磁无刷电机的变网络等效磁路模型[J]. 电工技术学报, 2016, 31(17): 147-153.
Xu Yanliang, Wu Qiaobian, Gong Xiao.Network- varying equivalent magnetic circuit modeling of novel disk transverse-flux permanent magnet brush- less machine[J]. Transactions of China Electro- technical Society, 2016, 31(17): 147-153.
[12] Adeeb A, Iqbal H.Power factor improvement of a transverse flux machine with high torque density[J]. IEEE Transactions on Industry Applications, 2018, 54(5): 4297-4305.
[13] 徐衍亮, 崔波, 张文晶, 等. 软磁复合材料-Si钢组合铁心盘式横向磁通永磁无刷电机[J]. 电工技术学报, 2020, 35(5): 983-990.
Xu Yanliang, Cui Bo, Zhang Wenjing, et al.Disk transverse flux permanent magnet brushless motor based on soft magnetic composite-Si steel core[J]. Transactions of China Electrotechnical Society, 2020, 35(5): 983-990.
[14] 卢琴芬, 谢舸, 金勇, 等. 混合铁心横向磁通永磁电机的设计与分析[J]. 中国电机工程学报, 2011, 31(9): 68-72.
Lu Qinfen, Xie Ke, Jin Yong, et al.Design and analysis of a transverse-flux permanent magnet motor with hybrid iron-core[J]. Proceedings of the CSEE, 2011, 31(9): 68-72.
[15] Agrawal S, Dashora Y, Tiwari M K, et al.Interactive particle swarm: a pareto-adaptive metaheuristic to multiobjective optimization[J]. IEEE Transactions on Systems Man & Cybernetics Part A Systems & Humans, 2008, 38(2): 258-277.
[16] 周念成, 肖舒严, 虞殷树, 等. 基于质心频率和BP神经网络的配网故障测距[J]. 电工技术学报, 2018, 33(17): 4154-4166.
Zhou Niancheng, Xiao Shuyan, Yu Yinshu, et al.Fault location in distribution networks based on centroid frequency and BP neural networks[J]. Transactions of China Electrotechnical Society, 2018, 33(17): 4154-4166.
[17] Yu Shiwei, Zhu Kejun, Diao Fengqin.A dynamic all parameters adaptive BP neural networks model and its application on oil reservoir prediction[J]. Applied Mathematics & Computation, 2008, 195(1): 66-75.