Hybrid Analytical Model for Predicting the Electromagnetic Losses in Surface-Mounted Permanent-Magnet Motors

被引:2
作者
Li, Zhaokai [1 ]
Huang, Xiaoyan [2 ]
Ma, Jun [3 ]
Chen, Zhuo [2 ]
Liu, Ang [2 ]
Peretti, Luca [1 ]
机构
[1] KTH Royal Inst Technol, Dept Elect Engn, S-11428 Stockholm, Sweden
[2] Zhejiang Univ, Coll Elect Engn, Zhejiang Prov Key Lab Elect Machine Syst, Hangzhou 310027, Peoples R China
[3] Univ Bristol, Dept Elect & Elect Engn, Bristol BS8 1TH, England
来源
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION | 2024年 / 10卷 / 01期
基金
中国国家自然科学基金;
关键词
Iron; Analytical models; Magnetic losses; Saturation magnetization; Magnetic flux; Magnetic hysteresis; Magnetic fields; Electromagnetic losses; hybrid analytical model (HAM); surface-mounted permanent-magnet (PM) motor; EDDY-CURRENT LOSS; IRON LOSS; SYNCHRONOUS MOTORS; THERMAL-ANALYSIS; PERFORMANCE; HYSTERESIS; FIELD; METHODOLOGY; MACHINES;
D O I
10.1109/TTE.2023.3289869
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article presents a comprehensive method to predict the electromagnetic losses in surface-mounted permanent-magnet (PM) motors based on a hybrid analytical model (HAM). HAM will significantly improve the calculation speed compared with finite-element method (FEM) while keeping great accuracy, making it a competitive alternative for the analysis and optimization of PM motors. As the accurate field distribution is the bias of electromagnetic losses prediction, the magnet loss, sleeve loss, and copper loss can all be accurately obtained from their vector potential distribution using HAM with small computational burden. As for iron loss, the improved Jiles-Atherton (JA) model is proposed to build the relationship between the loss and the magnetic field in the iron region from the perspective of energy conversion. The predictions of magnet loss, sleeve loss, and copper loss using HAM agree well with the FEM. The experiment on surface-mounted PM prototype demonstrates the high accuracy of iron loss calculation using the combination of the improved JA model and HAM.
引用
收藏
页码:1388 / 1397
页数:10
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