부산대학교 도서관

Prediction of iron loss in electrical machines (e-machines) is known to be a challenging task. The concept of a building factor (BF) to account for the discrepancy between predicted and measured loss is widely used. From the literature, these BFs may need to be as high as 1.5–2, i.e., a discrepancy of up to 100%, leading to a different impact on total losses for every e-machine. To calibrate the BF, modeling, and testing are required. This article describes an extensive test campaign on permanent magnet synchronous machines (PMSMs) at no-load with magnetized and dummy rotors. Several challenges to accurately quantify no-load iron loss by dynamic testing for model calibration are reported, highlighting the benefits of rotor temperature monitoring, and performing repeatability checks. For accurate prediction of iron loss impacted by mechanical stress (due to cut edge damage or shrink-fit for example), advanced modeling approaches require electrical steel properties (BH and loss density) as a function of tensile and compressive stress. Such measurements with a dedicated single-sheet tester (SST) have not yet been standardized. Repeatability issues and the spread of measured data are presented and their influence is mitigated by a precycling procedure. A novel method to compare the impact of stress on several electrical steel grades including thicknesses from 0.1 to 0.35 mm indicates different grades follow similar trends. However, the changes are grade-specific, requiring characterization of each material grade at multiple stress levels, frequency, and flux density for advanced modeling of e-machine performance.