• DocumentCode
    3115226
  • Title

    Optimized design of induction motor parameters based on PSO (Particle Swarm Optimization)

  • Author

    Guo, Ping ; Huang, Dagui ; Feng, Daiwei ; Yu, Wenzheng ; Zhang, Hailong

  • Author_Institution
    Key Lab. of Minist. of Inf. Ind. Intell. Mech., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2012
  • fDate
    5-8 Aug. 2012
  • Firstpage
    837
  • Lastpage
    842
  • Abstract
    This paper elaborates using particle swarm optimization (PSO) algorithm to solve the problem that the operating efficiency of induction motor is too low. In this paper, optimizing the structure parameters for induction motor design is proposed. The presented method is based on the principle that the induction motor structure parameters have complex relationship with efficiency; its advantage is that it can find the optimized structure parameters to output maximum efficiency when the motor operates in some conditions. It is demonstrated PSO algorithm is so efficient in finding the optimum structure parameters; for avoiding the algorithm running into local optimization, this paper adjusts the inertia factor during the iterative process. The simulation result shows that using PSO algorithm can find out the optimum structure parameters.
  • Keywords
    induction motors; iterative methods; particle swarm optimisation; PSO algorithm; induction motor operating efficiency; induction motor parameters optimized design; induction motor structure parameters; iterative process; local optimization; optimized structure parameters; optimum structure parameters; output maximum efficiency; particle swarm optimization; Automation; Conferences; Mechatronics; induction motor; maximum efficiency; particle swarm optimization (PSO); structure parameter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2012 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4673-1275-2
  • Type

    conf

  • DOI
    10.1109/ICMA.2012.6283251
  • Filename
    6283251