高速永磁电机新型磁性复合材料弹性模量预测

doi:10.19595/j.cnki.1000-6753.tces.231481

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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.

Key words： High-speed motor composite rotor composite magnetic materials elastic modulus numerical simulation

Received: 08 September 2023

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TM355

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	Wang Tianyu
	Yang Luming
	Bai Bin
	Yu Qiuhong
	Zhang Yue

Cite this article:

Wang Tianyu,Yang Luming,Bai Bin等. Elastic Modulus Prediction of Novel Magnetic Composites for High-Speed Permanent Magnet Motors[J]. Transactions of China Electrotechnical Society, 2024, 39(20): 6305-6315.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.231481 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/I20/6305

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