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Velocity-Controlled Particle Swarm Optimization (PSO) and Its Application to the Optimization of Transverse Flux Induction Heating Apparatus

Author

Listed:
  • Youhua Wang

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Bin Li

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Liuxia Yin

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Jiancheng Wu

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Shipu Wu

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Chengcheng Liu

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
    Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China)

Abstract

The main disadvantage of transverse flux induction heating (TFIH) is its resulting non-uniform temperature distribution on the surface of the strip at the inductor outlet. For obtaining a uniform temperature distribution, an improved particle swarm optimization (PSO) named velocity-controlled PSO (VCPSO) is proposed and applied to optimize this problem. Support vector machine (SVM) is adopted to establish a regression model to replace the complex and time-consuming coupling calculation process involved in TFIH problem. Simulation results of several test functions show that VCPSO performs much better than standard PSO (SPSO). Moreover, based on the existing research and experiments, the application of VCPSO combined with SVM to the TFIH problem achieves satisfactory results.

Suggested Citation

  • Youhua Wang & Bin Li & Liuxia Yin & Jiancheng Wu & Shipu Wu & Chengcheng Liu, 2019. "Velocity-Controlled Particle Swarm Optimization (PSO) and Its Application to the Optimization of Transverse Flux Induction Heating Apparatus," Energies, MDPI, vol. 12(3), pages 1-12, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:487-:d:203238
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    Citations

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    Cited by:

    1. Wei Han & Kwok Tong Chau & Hoi Chun Wong & Chaoqiang Jiang & Wong Hing Lam, 2019. "All-In-One Induction Heating Using Dual Magnetic Couplings," Energies, MDPI, vol. 12(9), pages 1-17, May.
    2. Huabin Song & Youhua Wang & Jiangpai Peng & Chengcheng Liu, 2022. "Study on the Uniformity of Temperature Distribution of Transverse Flux Induction Heating Based on a New Magnetic Pole," Energies, MDPI, vol. 15(19), pages 1-15, October.
    3. Hyung-Joon Kim & Mun-Kyeom Kim, 2019. "Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response," Energies, MDPI, vol. 12(21), pages 1-28, October.

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