Elastic Modulus Prediction of Novel Magnetic Composites for High-Speed Permanent Magnet Motors
Wang Tianyu1, Yang Luming2, Bai Bin2, Yu Qiuhong3, Zhang Yue4
1. School of Mechanical and Energy Engineering Shanghai Technical Institute of Electronics & Information Shanghai 201411 China; 2. School of Mechanical Engineering Shenyang Institute of Technology Shenyang 110136 China; 3. Shenyang Yuheng Technology Co. Ltd Shenyang 110122 China; 4. School of Electrical Engineering Shandong University Jinan 250100 China
Abstract：The tensile strength of the conventional surface mount HSPMM (High-speed permanent magnet motor) rotor's permanent magnet is significantly low, posing a bottleneck for developing HSPMM. A novel composite rotor structure incorporating a powder block layer can effectively enhance the rotor strength of HSPMMs. The mechanical properties of these new composite magnetic materials play a crucial role in ensuring the structural strength and performance of magnetic components. Unlike traditional HSPMM rotors, the composite rotor structure consists of multiple layers of composite magnetic materials, necessitating a different approach to accurately analyze its mechanical strength. This paper employs micromechanics and finite element method techniques to predict the elastic modulus of magnetic composites based on an equivalent three-phase spherical model. Furthermore, the influence of microstructure, interface parameters, and magnetic powder grade on the elastic modulus of the magnetic powder film (MPF) is studied, and a mapping relationship between microstructure and mechanical properties is established. Firstly, a representative volume element (RVE) calculation model is constructed for the MPF to capture its real microstructure. From a microscopic perspective, MPF is regarded as a three-phase composite material comprising magnetic particles, interface layers, and resin matrix. The Monte-Carlo method and Python language are utilized to develop the Abaqus software kernel for automating random particle generation, Boolean cutting and merging operations, and grid division. By adjusting parameters such as particle size, gradation, group distribution ratio, and interface layer thickness, mesoscale models representing different magnetic powder components are generated to establish the mapping relationship between mesoscopic structure and material properties. Secondly, the parameters of the interface in the RVE model are determined using elastic mechanics theory and Eshelby equivalent theory based on critical magnetic particle content. Crucial information, such as the interface layer's thickness, volume fraction, and elastic modulus, can be obtained. The proposed method ensures a uniform distribution of spherical particles at all levels. Finally, based on the virtual work principle, a finite element prediction model for the elastic modulus of the magnetic powder film is established. The predicted results can be effectively utilized in the structural design and analysis of magnetic composite materials, allowing rapid prediction of mechanical properties without complex, time-consuming testing procedures. Based on the finite element model of micromechanics, the mechanical properties of magnetic materials are simulated and analyzed. The effects of magnetic particle gradation, interface layer parameters, and interface elastic modulus on the elastic modulus of magnetic materials are studied. The following conclusions can be drawn from the simulation analysis. (1) Magnetic particle gradation, interfacial layer parameters, and interfacial elastic modulus significantly influence the elastic modulus of MPF. Adjusting these microstructure parameters using a predictive model make it possible to enhance the material's mechanical properties. (2) Optimizing the gradation of magnetic powder using the proposed prediction model can improve the MPF elastic modulus when keeping the integral number of magnetic powder constant. (3) Accurate calculation of interface layer parameters can effectively enhance the accuracy of the prediction model.
王天煜, 杨璐铭, 白斌, 宇秋红, 张岳. 高速永磁电机新型磁性复合材料弹性模量预测[J]. 电工技术学报, 2024, 39(20): 6305-6315.
Wang Tianyu, Yang Luming, Bai Bin, Yu Qiuhong, Zhang Yue. Elastic Modulus Prediction of Novel Magnetic Composites for High-Speed Permanent Magnet Motors. Transactions of China Electrotechnical Society, 2024, 39(20): 6305-6315.
[1] 鲍旭聪, 王晓琳, 彭旭衡, 等. 高速电机驱动关键技术研究综述[J]. 中国电机工程学报, 2022, 42(18): 6856-6871. Bao Xucong, Wang Xiaolin, Peng Xuheng, et al.Review of key technologies of high-speed motor drive[J]. Proceedings of the CSEE, 2022, 42(18): 6856-6871. [2] 杨江涛, 王镇宇, 冯垚径, 等. 高速永磁电机转子过盈方式对转子应力的影响[J]. 电工技术学报, 2023, 38(16): 4263-4273. Yang Jiangtao, Wang Zhenyu, Feng Yaojing, et al.Influence of shrink fitting modes on rotor stress of high speed permanent magnet machine[J]. Transactions of China Electrotechnical Society, 2023, 38(16): 4263-4273. [3] 戴睿, 张岳, 王惠军, 等. 基于多物理场近似模型的高速永磁电机多目标优化设计[J]. 电工技术学报, 2022, 37(21): 5414-5423. Dai Rui, Zhang Yue, Wang Huijun, et al.Multi-objective optimization design of high-speed permanent magnet machine based on multi-physics approximate model[J]. Transactions of China Electrotechnical Society, 2022, 37(21): 5414-5423. [4] Qin Xuefei, Shen Jianxin, Nilssen R, et al.Design of high-speed PMSM considering multi-physics fields and power converter constraints[J]. Journal of Electrotechnical Society, 2022, 37(7): 1618-1633. [5] 曹龙飞, 范兴纲, 李大伟, 等. 基于快速有限元的永磁电机绕组涡流损耗半解析高效计算[J]. 电工技术学报, 2023, 38(1): 153-165. Cao Longfei, Fan Xinggang, Li Dawei, et al.Semi analytical and efficient calculation method of eddy current loss in windings of permanent magnet machines based on fast finite element method[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 153-165. [6] 张文校, 胡岩, 曹力, 等. 高速永磁屏蔽电机摩擦损耗分析与计算[J]. 电工技术学报, 2023, 38(12): 3122-3129. Zhang Wenxiao, Hu Yan, Cao Li, et al.Analysis and calculation of friction loss of high-speed permanent magnetic shielding motor[J]. Transactions of China Electrotechnical Society, 2023, 38(12): 3122-3129. [7] Wang Zerun, Zhang Yue, Wang Tianyu, et al.Analytical model of mechanical properties of carbon fiber magnetic powder film-level magnetic materials for high-speed motors[J]. Energy Reports, 2022, 8: 374-383. [8] Sato M, Takazawa K, Horiuchi M, et al.Reducing rotor temperature rise in concentrated winding motor by using magnetic powder mixed resin ring[J]. Energies, 2020, 13(24): 6721. [9] Yao Jinyu, Wang Huijun, Zhang Yue, et al.Magnetic properties analysis of novel composite magnetic materials for HSPMSMs[J]. IEEE Transactions on Magnetics, 2022, 58(4): 8104310. [10] 田学亮, 徐颖. 碳化硅颗粒增强铝基复合材料有效弹性模量预测[J]. 航空发动机, 2021, 47(5): 92-97. Tian Xueliang, Xu Ying.Prediction of effective elastic modulus for SiC particle reinforced aluminium matrix composites[J]. Aeroengine, 2021, 47(5): 92-97. [11] 李庆, 杨晓翔. 颗粒增强橡胶细观力学性能二维数值模拟[J]. 应用力学学报, 2012, 29(5): 607-612, 633. Li Qing, Yang Xiaoxiang.Two-dimensional numerical simulation for mechanical behavior of particle reinforced rubber matrix composites[J]. Chinese Journal of Applied Mechanics, 2012, 29(5): 607-612, 633. [12] 邵乐天, 尧军平, 胡启耀, 等. 颗粒尺寸对TiC/AZ91镁基复合材料力学性能的影响[J]. 材料热处理学报, 2019, 40(9): 1-7. Shao Letian, Yao Junping, Hu Qiyao, et al.Effect of particle size on mechanical properties of TiC/AZ91 magnesium matrix composites[J]. Transactions of Materials and Heat Treatment, 2019, 40(9): 1-7. [13] Meng Qinghua, Wang Zhenqing.Prediction of interfacial strength and failure mechanisms in particle-reinforced metal-matrix composites based on a micromechanical model[J]. Engineering Fracture Mechanics, 2015, 142: 170-183. [14] 刘骏华, 张娟, 张晨, 等. 颗粒增强金属基复合材料细观有限元建模方法的对比[J]. 机械工程材料, 2022, 46(4): 82-88, 94. Liu Junhua, Zhang Juan, Zhang Chen, et al.Comparison of meso finite element modeling methods for particle reinforced metal matrix composites[J]. Materials for Mechanical Engineering, 2022, 46(4): 82-88, 94. [15] 邱昆, 姜云鹏, 史雪萍, 等. 新型颗粒增强金属玻璃复合材料的拉伸增韧机制[J]. 复合材料学报, 2018, 35(1): 124-131. Qiu Kun, Jiang Yunpeng, Shi Xueping, et al.Tensile toughening mechanism of new particle reinforced metallic glass composites[J]. Acta Materiae Compositae Sinica, 2018, 35(1): 124-131. [16] 田玉泰. 基于Python的Abaqus前、后处理GUI插件二次开发与应用[J]. 计算机辅助工程, 2022, 31(2): 63-68. Tian Yutai.GUI plugin redevelopment and application of Abaqus pre-and post-processing based on Python[J]. Computer Aided Engineering, 2022, 31(2): 63-68. [17] 吴宇航, 肖映雄, 徐亚飞. 基于Python-Abaqus的混凝土三维细观随机模型的建立[J]. 计算力学学报, 2022, 39(5): 566-573. Wu Yuhang, Xiao Yingxiong, Xu Yafei.Establishment of mesoscopic stochastic models of concrete in three dimensions based on Python-Abaqus[J]. Chinese Journal of Computational Mechanics, 2022, 39(5): 566-573. [18] 吴鑫森, 陈祥宝, 宋焕成. 颗粒增强复合材料中的界面层[J]. 复合材料学报, 1985, 2(3): 41-45, 118. Wu Xinsen, Chen Xiangbao, Song Huancheng.Interface layer in particulate composites[J]. Acta Materiae Compositae Sinica, 1985, 2(3): 41-45, 118. [19] Li Guoqiang, Zhao Yi, Pang Suseng.Four-phase sphere modeling of effective bulk modulus of concrete[J]. Cement and Concrete Research, 1999, 29(6): 839-845. [20] Yao Jinyu, Zhang Yue, Wang Huijun, et al.Effect of multi-size magnetic powder gradation on magnetic properties of novel composite magnetic materials for HSPMSM[J]. IEEE Transactions on Transportation Electrification, 2022, 8(3): 3594-3605. [21] 史平安, 万强, 张灿阳, 等. 铁凝胶的力磁耦合细观力学模型的建立[J]. 机械强度, 2017, 39(3): 564-571. Shi Ping’an, Wan Qiang, Zhang Canyang, et al.Study on the micromechanical model of force-magnetic coupling for ferrogel materials[J]. Journal of Mechanical Strength, 2017, 39(3): 564-571.
2024, Vol. 39 
