Determination of induction motor parameters with differential evolution algorithm

被引:0
|
作者
Mustafa Arslan
Mehmet Çunkaş
Tahir Sağ
机构
[1] Selcuk University,Technical Sciences Vocational School, Electrical Department
[2] Selcuk University,Faculty of Technical Education, Electronics and Computer Education
来源
关键词
Inductions motor; Parameter determination; Differential evolution algorithm; Genetic algorithm;
D O I
暂无
中图分类号
学科分类号
摘要
In this study, the determination of equivalent circuit parameters of induction motors is carried out with differential evolution algorithm (DEA) and genetic algorithm (GA). As an objective function in the algorithms, the sum torque error at zero speed, pull-out, and rated speed is used. The determination of equivalent circuit parameters is performed with three induction motors of 2.2, 5.5, and 37 kW. In particular, the search ability of DEA is compared with GA by using the same population size, number of iteration, and crossover rate. In addition, the effects of the obtained equivalent circuit parameters on induction motors characteristics are investigated and presented with graphics. The results show that the use of DEA instead of GA increases the convergence sensitivity and reduces the simulation time.
引用
收藏
页码:1995 / 2004
页数:9
相关论文
共 50 条
  • [31] Differential Evolution Algorithm with Ensemble of Parameters and Mutation and Crossover Strategies
    Mallipeddi, Rammohan
    Suganthan, Ponnuthurai Nagaratnam
    SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, 2010, 6466 : 71 - +
  • [32] Parameters Identification of Photovoltaic Cells Based on Differential Evolution Algorithm
    Hui, Liao
    Qiao-Dongkai
    Lin, Huang-Chong
    Dong, Li-Shi
    3RD ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND APPLICATIONS (ITA 2016), 2016, 7
  • [33] Identification of A Hysteresis Model Parameters Using the Differential Evolution Algorithm
    Liu Shiming
    Liu Ruisheng
    Dong Liang
    Guo Yu
    2017 2ND ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2017), 2017, 199
  • [34] In-situ induction motor efficiency determination using the genetic algorithm
    Pillay, P
    Levin, V
    Otaduy, P
    Kueck, J
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 1998, 13 (04) : 326 - 333
  • [35] Study on Aggregation of Inductive Motor Loads Based on Differential Evolution Algorithm
    Zhang, Baozhen
    Fan, Chenxi
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING AND STATISTICS APPLICATION (AMMSA 2017), 2017, 141 : 365 - 368
  • [36] Neighbor-Induction and Population-Dispersion in Differential Evolution Algorithm
    Miao, Kun
    Wang, Ziyang
    IEEE ACCESS, 2019, 7 : 146358 - 146378
  • [37] A Differential Evolution Algorithm for Designing Inverter-Driven Induction Motors
    Pina, Alejandro J.
    Xu, Longya
    2014 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), 2014, : 279 - 286
  • [38] Identification of induction motor parameters
    Pappano, V
    Lyshevski, SE
    Friedland, B
    PROCEEDINGS OF THE 37TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4, 1998, : 989 - 994
  • [39] Observation of induction motor parameters
    Bahi, T
    Rais, T
    Debbache, NE
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2005, 77 (05): : 384 - 387
  • [40] Estimation of induction motor parameters based on field test coupled with genetic algorithm
    Phumiphak, T
    Chat-uthai, C
    POWERCON 2002: INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS 1-4, PROCEEDINGS, 2002, : 1199 - 1203