IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i13p3395-d379365.html
   My bibliography  Save this article

Optimal Design of IPMSM for FCEV Using Novel Immune Algorithm Combined with Steepest Descent Method

Author

Listed:
  • Ji-Chang Son

    (School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea)

  • Young-Rok Kang

    (School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea)

  • Dong-Kuk Lim

    (School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea)

Abstract

In this paper, the Novel Immune Algorithm (NIA) is proposed for an optimal design of electrical machines. By coupling the conventional Immune Algorithm and Steepest Descent Method, the NIA can perform fast and exact convergence to both global solutions and local solutions. Specifically, the concept of an antibody radius is newly introduced to improve the ability to navigate full areas effectively and to find new peaks by excluding already searched areas. The validity of the NIA is confirmed by mathematical test functions with complex objective function regions. The NIA is applied to an optimal design of an interior permanent magnet synchronous motor for fuel cell electric vehicles and to derive an optimum design with diminished torque ripple.

Suggested Citation

  • Ji-Chang Son & Young-Rok Kang & Dong-Kuk Lim, 2020. "Optimal Design of IPMSM for FCEV Using Novel Immune Algorithm Combined with Steepest Descent Method," Energies, MDPI, vol. 13(13), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3395-:d:379365
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/13/3395/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/13/3395/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chao Wu & Jun Yang & Qi Li, 2020. "GPIO-Based Nonlinear Predictive Control for Flux-Weakening Current Control of the IPMSM Servo System," Energies, MDPI, vol. 13(7), pages 1-21, April.
    2. Quan Yin & Haichun Li & Hui Luo & Qingyi Wang & Chendong Xu, 2020. "An Improved Sensorless Vector Control Method for IPMSM Drive with Small DC-Link Capacitors," Energies, MDPI, vol. 13(3), pages 1-26, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ji-Chang Son & Myung-Ki Baek & Sang-Hun Park & Dong-Kuk Lim, 2021. "Improved Immune Algorithm Combined with Steepest Descent Method for Optimal Design of IPMSM for FCEV Traction Motor," Energies, MDPI, vol. 14(13), pages 1-12, June.
    2. Mitsuhide Sato & Keigo Takazawa & Manabu Horiuchi & Ryoken Masuda & Ryo Yoshida & Masami Nirei & Yinggang Bu & Tsutomu Mizuno, 2020. "Reducing Rotor Temperature Rise in Concentrated Winding Motor by Using Magnetic Powder Mixed Resin Ring," Energies, MDPI, vol. 13(24), pages 1-15, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ji-Chang Son & Myung-Ki Baek & Sang-Hun Park & Dong-Kuk Lim, 2021. "Improved Immune Algorithm Combined with Steepest Descent Method for Optimal Design of IPMSM for FCEV Traction Motor," Energies, MDPI, vol. 14(13), pages 1-12, June.
    2. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    3. Alessandro Benevieri & Lorenzo Carbone & Simone Cosso & Krishneel Kumar & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2022. "Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review," Energies, MDPI, vol. 15(20), pages 1-26, October.
    4. Zhuo Liu & Azeddine Houari & Mohamed Machmoum & Mohamed-Fouad Benkhoris & Tianhao Tang, 2020. "An Active FTC Strategy Using Generalized Proportional Integral Observers Applied to Five-Phase PMSG based Tidal Current Energy Conversion Systems," Energies, MDPI, vol. 13(24), pages 1-22, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3395-:d:379365. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.