ORGANIZATION : Intermag-MMM
JOURNAL :
YEAR : 2016.01
VOL :
PAGE : -
Electrical steel sheets have a hysteresis phenomenon. This characteristic appears as initial magnetization curves (B-H curves) and it
differs each classification. For the same steel sheet, however, B-H curve changes according to the manufacturing process. Consequently,
there exist standardized measurement process of measuring the magnetic property and Epstein frame is international standard [1]. In
electric motor application, stator yoke properties of electric motors are similar to the ring core. For this reason, the ring core specimen
test is more appropriate method [2].
To acquire B-H curves from Epstein frame and the ring core specimen, the ring core specimen is manufactured. The constraint on the
ring core specimen specification, ensuring the reliability of test results is outer diameter should be in 1.1~1.4 times of inner diameter
[3]. From the manufactured ring core specimen and conventional Epstein frame, measure the each B-H curve. Comparison of these
curves is in Fig. 1 and it shows the difference between manufacturing processes. In this paper, predict the no load electric motor
performance through finite element analysis (FEA) using the ring core B-H curve. Furthermore, acquire iron losses from the ring core
specimen along different frequencies to generate the iron loss map and applying them to predict the electric motor performance more
accurately.
The 8poles 12slots surface mounted permanent magnet synchronous motor (SPMSM) is adopted to validate the previously acquired
data. Obtain the no load back electromotive force (EMF) from FEA and Fig. 2 shows a comparison of no load back EMF between
experiment result and FEA results using Epstein frame and the ring core specimen B-H curve [4]. An error between the experiment
result and FEA results of Epstein frame and the ring core specimen is 3.8% and 0.6% respectively. As a future work, additionally
acquire iron losses along different frequencies from the ring core specimen and applying them to predict the electric motor
performance map.