Comparison of Iron Loss Models for Electrical Machines With Different Frequency Domain and Time Domain Methods for Excess Loss Prediction

被引:44
|
作者
Kowal, Damian [1 ]
Sergeant, Peter [1 ,2 ]
Dupre, Luc [1 ]
Vandenbossche, Lode [3 ]
机构
[1] Univ Ghent, Dept Elect Energy Syst & Automat, B-9000 Ghent, Belgium
[2] Univ Ghent, Dept Ind Technol & Construct, B-9000 Ghent, Belgium
[3] ArcelorMittal Global Res & Dev Gent, B-9060 Zelzate, Belgium
关键词
Electrical steel; excess losses; iron losses; loss modeling; DYNAMIC PREISACH MODEL; INDUCTION WAVE-FORM;
D O I
10.1109/TMAG.2014.2338836
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
The goal of this paper is to investigate the accuracy of modeling the excess loss in electrical steels using a time domain model with Bertotti's loss model parameters n(0) and V-0 fitted in the frequency domain. Three variants of iron loss models based on Bertotti's theory are compared for the prediction of iron losses under sinusoidal and non-sinusoidal flux conditions. The non-sinusoidal waveforms are based on the realistic time variation of the magnetic induction in the stator core of an electrical machine, obtained from a finite element-based machine model.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Comparison of different models for iron core loss calculation in electrical machines
    Stumberger, B
    Gorican, V
    Hamler, A
    Trlep, M
    Jesenik, M
    ELECTROMAGNETIC FIELDS IN ELECTRICAL ENGINEERING, 2002, 22 : 283 - 288
  • [2] Accuracy of iron loss calculation in electrical machines by using different iron loss models
    Stumberger, B
    Gorican, V
    Stumberger, G
    Hamler, A
    Trlep, M
    Jesenik, M
    JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS, 2003, 254 : 269 - 271
  • [3] Evaluation of Iron Loss Models in Electrical Machines
    Zhu, Z. Q.
    Xue, Shaoshen
    Feng, Jianghua
    Guo, Shuying
    Chen, Zhichu
    Peng, Jun
    Chu, W. Q.
    2017 20TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS), 2017,
  • [4] Evaluation of Iron Loss Models in Electrical Machines
    Zhu, Zi-Qiang
    Xue, Shaoshen
    Chu, Wenqiang
    Feng, Jianghua
    Guo, Shuying
    Chen, Zhichu
    Peng, Jun
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2019, 55 (02) : 1461 - 1472
  • [5] Prediction of mechanical stress effects on the iron loss in electrical machines
    Ali, K
    Atallah, K
    Howe, D
    JOURNAL OF APPLIED PHYSICS, 1997, 81 (08) : 4119 - 4121
  • [6] Prediction of mechanical stress effects on the iron loss in electrical machines
    Ali, K.
    Atallah, K.
    Howe, D.
    Journal of Applied Physics, 1997, 81 (8 pt 2A)
  • [7] Repeatability of Tests for Validation of Iron Loss Models in Electrical Machines
    Soulard, J.
    Ma, X. Y.
    Griffin, E.
    Silvester, B.
    IEEE TRANSACTIONS ON MAGNETICS, 2023, 59 (11)
  • [8] Time and Frequency Domain Description of Gilbert-Elliott Data Loss Models
    Palko, Andras
    Sujbert, Laszlo
    2019 20TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC), 2019, : 606 - 611
  • [9] Comparison of different clinical models of cerebral autoregulation in time and frequency domain
    Kozusko, J.
    Noack, F.
    Christ, M.
    Morgenstern, U.
    WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, VOL 25, PT 4: IMAGE PROCESSING, BIOSIGNAL PROCESSING, MODELLING AND SIMULATION, BIOMECHANICS, 2010, 25 : 938 - 941
  • [10] Comparison of machine learning models based on time domain and frequency domain features for faults diagnosis in rotating machines
    Sepulveda, Natalia Espinoza
    Sinha, Jyoti
    14TH INTERNATIONAL CONFERENCE ON VIBRATION ENGINEERING AND TECHNOLOGY OF MACHINERY (VETOMAC XIV), 2018, 211