Combined FE and Particle Swarm algorithm for optimization of high speed PM synchronous machine

被引:10
|
作者
Belahcen, Anouar [1 ]
Martin, Floran [1 ]
Zaim, Mohammed El-Hadi [2 ]
Dlala, Emad [3 ]
Kolondzovski, Zlatko [4 ]
机构
[1] Aalto Univ, Dept Elect Engn & Automat, Aalto, Finland
[2] Polytech Nantes, IREENA, St Nazaire, France
[3] ANSYS Inc, Ann Arbor, MI USA
[4] ABB Machines, Helsinki, Finland
基金
芬兰科学院;
关键词
Optimization techniques; Finite element simulation; Electric machines; MULTIOBJECTIVE OPTIMIZATION; METHODOLOGY;
D O I
10.1108/COMPEL-07-2014-0168
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Purpose - The purpose of this paper is to optimize the stator slot geometry of a high-speed electrical machine, which is used as an assist for a turbocharger. Meanwhile, the suitability of the Particle Swarm algorithm for such a problem is to be tested. Design/methodology/approach - The starting point of the optimization is an existing design, for which the Particle Swarm algorithm is applied in conjunction with the transient time-stepping 2D finite element method. Findings - It is found that regardless of its stochastic nature, the Particle Swarm work well for the optimization of electrical machines. The optimized design resulted in an increase of the slot area and increase of the iron loss, which was compensated by a dramatic decrease in the Joule losses. Research limitations/implications - The optimization was concentrated on the stator design whereas the rotor dimensioning was carried out withing the compressor and turbine design. Originality/value - A turbocharger with electric assist is designed optimized and manufactured. The Particle Swarm algorithm is shown to be very stable.
引用
收藏
页码:475 / 484
页数:10
相关论文
共 50 条
  • [1] Synchronous Machine Parameters Evaluation with a Hybrid Particle Swarm Optimization Algorithm
    Araujo, Bruno Tonsic
    Bernardes, Jose Vitor, Jr.
    Bortoni, Edson da Costa
    Lambert-Torres, Germano
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2017, 45 (17) : 1962 - 1971
  • [2] Prediction of twisting Machine Speed based on improved Particle Swarm Optimization algorithm
    Wang, Yannian
    Zhai, Weixun
    Li, Xiongfei
    Zhong, Zheng
    2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY RESOURCES AND ENVIRONMENT ENGINEERING (ICAESEE 2019), 2020, 446
  • [3] Design of high-performance plasmonic nanosensors by particle swarm optimization algorithm combined with machine learning
    Yan, Ruoqin
    Wang, Tao
    Jiang, Xiaoyun
    Zhong, Qingfang
    Huang, Xing
    Wang, Lu
    Yue, Xinzhao
    NANOTECHNOLOGY, 2020, 31 (37)
  • [5] Particle filter algorithm optimized by genetic algorithm combined with particle swarm optimization
    Yang, Jin
    Cui, Xuerong
    Li, Juan
    Li, Shibao
    Liu, Jianhang
    Chen, Haihua
    2020 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI2020), 2021, 187 : 206 - 211
  • [6] A Combined Local Best Particle Swarm Optimization Algorithm
    Lian, Zhigang
    Gao, Yejun
    Ji, Chunlei
    Wang, Xuewu
    MEASUREMENT TECHNOLOGY AND ENGINEERING RESEARCHES IN INDUSTRY, PTS 1-3, 2013, 333-335 : 1388 - +
  • [7] A particle swarm optimization algorithm for part-machine grouping
    Andres, Carlos
    Lozano, Sebastian
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2006, 22 (5-6) : 468 - 474
  • [8] OPTIMIZATION WITH PARTICLE SWARM AND GENETIC ALGORITHM OF FLUX REVERSAL MACHINE
    Boulayoune, Ahcene
    Guerroudj, Cherif
    Saou, Rachid
    Moreau, Luc
    Zaim, Mohamed El-Hadi
    REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE, 2017, 62 (01): : 19 - 24
  • [9] Genetic Algorithm and Particle Swarm Optimization Combined with Powell Method
    Bento, David
    Pinho, Diana
    Pereira, Ana I.
    Lima, Rui
    11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013, PTS 1 AND 2 (ICNAAM 2013), 2013, 1558 : 578 - 581
  • [10] A dynamic global and local combined particle swarm optimization algorithm
    Jiao, Bin
    Lian, Zhigang
    Chen, Qunxian
    CHAOS SOLITONS & FRACTALS, 2009, 42 (05) : 2688 - 2695