Winding Loss Separation in Thermal Analysis of Electromagnetic Devices

被引:0
作者
Wrobel, Rafal [1 ,2 ]
Simpson, Nick [1 ]
机构
[1] Univ Bristol, Dept Elect Engn, Bristol BS8 1TR, Avon, England
[2] Motor Design Ltd, Ellesmere SY12 0EG, England
来源
2016 XXII INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES (ICEM) | 2016年
关键词
Thermal analysis; winding power loss; end-winding power loss; loss separation; electrical machines; ELECTRICAL MACHINES;
D O I
暂无
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 paper investigates various winding loss separation approaches applicable to the thermal analysis of electrical machines, transformers and wound passive components. The accurate temperature prediction and identification of hot-spots within such electromagnetic devices is strongly dependent on the absolute power loss data as well as the loss distribution within the subassemblies or regions of the device. The losses within a device are often defined as the average loss over a particular region, for example, the winding loss, core loss or magnet loss. However, such a loss definition might not yield the required fidelity or resolution, particularly if localised power loss such as ac winding loss is present during device operation. To account for the inhomogeneous winding loss, a more detailed loss separation is required. In this paper, the winding subassembly is subdivided into a number of sub-regions accounting for both the active length and end-winding. Three-dimensional (3D) electromagnetic and thermal analyses are employed to give insight into the effect of the loss definition on the accuracy and validity of the temperature prediction. A hardware exemplar representative of a single-layer open-slot stator/winding subassembly has been selected for the analysis. The results suggests that detailed loss separation provides improved accuracy of the temperature predictions and hotspots identification when compared with the more common averaged loss definition. The theoretical findings have been validated with experimental data showing close correlation.
引用
收藏
页码:2133 / 2139
页数:7
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