Abstract The magnetostrictive phenomenon in the electrical steel is an important cause of vibration of the iron core in motors and transformers. Magnetostrictive characteristics are close related to magnetization patterns of iron cores. There is a large amount of rotating magnetic field in the stator core of electric machines, and compared with alternating magnetization, the rotating magnetization will cause greater magnetostrictive strain. Therefore, accurately modeling the magnetostrictive characteristics in an electrical steel sheet under rotating magnetization is the basis and premise for optimizing the performance of electrical equipment. In this paper, using the Jiles-Atherton (J-A) hysteresis model to characterize the hysteresis behavior caused by the movement of the magnetic domain wall and the rotation of the magnetic moment during the magnetization process, a magnetostrictive model that can describe the vector and hysteresis characteristics of magnetostrictive normal and shear strains under rotating magnetization is proposed. Based on the characteristic data in an electrical steel sheet provided by the rotating magnetic characteristic measurement system, the particle swarm optimization algorithm was used to identify model parameters, and the accuracy of the model was verified. A measurement system of local magnetostrictive properties in silicon laminated cores was set up, and the specific process of calculating the magnetostrictive deformation of the core was presented. By comparing with the measurement results, the validity of the model was further investigated. It is shown that the magnetostriction of electrical steel sheets under rotating magnetization has hysteresis behavior, and the proposed model can effectively predict this kind of characteristics.
Li Daiyan,Zhang Yanli,Jing Ying等. Modeling of Magnetostrictive Characteristics in an Electrical Steel Sheet Based on the J-A Model and Its Experimental Verification[J]. Transactions of China Electrotechnical Society, 2022, 37(20): 5081-5091.
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2022, Vol. 37 
