MODELING OF THE SATURATED LEAKAGE REACTANCE OF INDUCTION-MOTORS AS A TIME-VARYING PARAMETER FOR TRANSIENT COMPUTATIONS

被引:5
|
作者
AKBABA, M
机构
[1] Department of Electrical Engineering College of Engineering, The University of Bahrain, Isa Town
来源
ELECTRIC MACHINES AND POWER SYSTEMS | 1992年 / 20卷 / 05期
关键词
D O I
10.1080/07313569208909616
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
A procedure has been developed for incorporating the saturated leakage reactance of induction motors into starting transient performance evaluation. An empirical formula has been provided for simulating the envelope of the transient current in terms of time. This faciliated to express the transient rms stator winding current in terms of time. Then saturated leakage reactance is expressed in terms of the transient rms stator winding current, which in turn, made it possible to express the leakage reactance as a time varying parameter. All types of slot openings, i.e., closed slots, semi closed slots and open slots are considered separately. Transient performance of a machine having closed slots on the rotor and semi closed slots on the stator is evaluated using the approach described in this article and the effect of leakage path saturation is demonstrated.
引用
收藏
页码:539 / 548
页数:10
相关论文
共 50 条
  • [41] Impulsive discrete-time BAM neural networks with random parameter uncertainties and time-varying leakage delays: an asymptotic stability analysis
    C. Sowmiya
    R. Raja
    J. Cao
    G. Rajchakit
    Nonlinear Dynamics, 2018, 91 : 2571 - 2592
  • [42] Robust rotor flux and speed control of induction motors using on-line time-varying rotor resistance adaptation
    Kenne, Godpromesse
    Ahmed-Ali, Tarek
    Nkwawo, Homere
    Lanmabhi-Lagarrigue, Francoise
    2005 44th IEEE Conference on Decision and Control & European Control Conference, Vols 1-8, 2005, : 7768 - 7774
  • [43] Real-Time Speed and Flux Adaptive Control of Induction Motors Using Unknown Time-Varying Rotor Resistance and Load Torque
    Kenne, Godpromesse
    Ahmed-Ali, Tarek
    Lamnabhi-Lagarrigue, Francoise
    Arzande, Amir
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2009, 24 (02) : 375 - 387
  • [44] A Modeling Approach With Spatial Basis Functions Learning and Temporal Dynamic Online Modeling for Time-Varying Distributed Parameter Processes
    Lu, Xinjiang
    Xu, Jie
    Zhou, Chao-Jun
    IEEE ACCESS, 2019, 7 : 137583 - 137593
  • [45] Time-varying dynamic modeling of micro-milling considering tool wear and the process parameter identification
    Ding, Pengfei
    Huang, Xianzhen
    Li, Yuxiong
    MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES, 2024, 52 (11) : 8658 - 8684
  • [46] Deep Learning-Based Time-Varying Parameter Identification for System-Wide Load Modeling
    Cui, Mingjian
    Khodayar, Mahdi
    Chen, Chen
    Wang, Xinan
    Zhang, Ying
    Khodayar, Mohammad E.
    IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (06) : 6102 - 6114
  • [47] A new approach for modeling hybrid systems based on the minimization of parameter transition in linear time-varying models
    Maruta, Ichiro
    Sugie, Toshiharu
    49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, : 1177 - 1182
  • [48] Robust Synchronization Criterion for Coupled Stochastic Discrete-Time Neural Networks with Interval Time-Varying Delays, Leakage Delay, and Parameter Uncertainties
    Park, M. J.
    Kwon, O. M.
    Park, Ju H.
    Lee, S. M.
    Cha, E. J.
    ABSTRACT AND APPLIED ANALYSIS, 2013,
  • [49] Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation
    Zhang, Jie
    Shi, Zhiyu
    Li, Lirong
    CHINESE JOURNAL OF AERONAUTICS, 2021, 34 (04) : 56 - 66
  • [50] Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation
    Jie ZHANG
    Zhiyu SHI
    Lirong LI
    Chinese Journal of Aeronautics , 2021, (04) : 56 - 66