IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i11p3215-d184050.html
   My bibliography  Save this article

Torque Ripple Reduction for Switched Reluctance Motor with Optimized PWM Control Strategy

Author

Listed:
  • Hui Cai

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Hui Wang

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Mengqiu Li

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Shiqi Shen

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Yaojing Feng

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Jian Zheng

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

The high current ripple and torque ripple are the main drawbacks of the switched reluctance motor (SRM) since the nonlinearity and double saliency, which limits its applications. In order to eliminate the current variation and torque ripple, an optimized pulse width modulation (PWM) control is presented in this paper. The voltage ratio duty is able to be predicted precisely according to the information of the motor running parameter. Based on torque sharing functions (TSFs), the current profile is pre-computed and four regions are defined according to the reference current profiles. The three modes, excitation, demagnetization and freewheeling, are flexibly chosen according to the characteristic of the current profile. It is indicated that it is better than that of conventional PWM modulation in terms of current ripple and the current tracing performance is improved without increasing the switching frequency or changing the hysteresis band. The current ripple is defined as the peak-to-peak value dividing the average value and it is reduced by 40%. A comparison in terms of the torque ripple and copper loss is also carried out: the torque ripple is significantly reduced via the proposed scheme under both magnetic linear and saturation conditions. The torque ripple and copper loss are reduced by about 70% and 12%, respectively. The validity and effectiveness of the proposed control strategy is verified by simulation and experimental results.

Suggested Citation

  • Hui Cai & Hui Wang & Mengqiu Li & Shiqi Shen & Yaojing Feng & Jian Zheng, 2018. "Torque Ripple Reduction for Switched Reluctance Motor with Optimized PWM Control Strategy," Energies, MDPI, vol. 11(11), pages 1-27, November.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3215-:d:184050
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/11/3215/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/11/3215/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu-Sung Yao, 2017. "Rapid Optimization of Double-Stators Switched Reluctance Motor with Equivalent Magnetic Circuit," Energies, MDPI, vol. 10(10), pages 1-20, October.
    2. Hye-Ung Shin & Kiwoo Park & Kyo-Beum Lee, 2015. "A Non-Unity Torque Sharing Function for Torque Ripple Minimization of Switched Reluctance Generators in Wind Power Systems," Energies, MDPI, vol. 8(10), pages 1-17, October.
    3. Yu Wang & Wenjuan Hao, 2018. "A Torque Impulse Balance Control for Multi-Tooth Fault Tolerant Switched-Flux Machines under Open-Circuit Fault," Energies, MDPI, vol. 11(7), pages 1-21, July.
    4. J. F. Pan & Weiyu Wang & Bo Zhang & Eric Cheng & Jianping Yuan & Li Qiu & Xiaoyu Wu, 2017. "Complimentary Force Allocation Control for a Dual-Mover Linear Switched Reluctance Machine," Energies, MDPI, vol. 11(1), pages 1-17, December.
    5. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    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. Peter Bober & Želmíra Ferková, 2020. "Comparison of an Off-Line Optimized Firing Angle Modulation and Torque Sharing Functions for Switched Reluctance Motor Control," Energies, MDPI, vol. 13(10), pages 1-13, May.
    2. Pulivarthi Nageswara Rao & Ramesh Devarapalli & Fausto Pedro García Márquez & Hasmat Malik, 2020. "Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor," Energies, MDPI, vol. 13(20), pages 1-38, October.

    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. Kang Wang & Ruituo Huai & Zhihao Yu & Xiaoyang Zhang & Fengjuan Li & Luwei Zhang, 2019. "Comparison Study of Induction Motor Models Considering Iron Loss for Electric Drives," Energies, MDPI, vol. 12(3), pages 1-13, February.
    2. Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.
    3. Jin Liu & Wenxiang Zhao & Jinghua Ji & Guohai Liu & Tao Tao, 2016. "A Novel Flux Focusing Magnetically Geared Machine with Reduced Eddy Current Loss," Energies, MDPI, vol. 9(11), pages 1-15, November.
    4. Zeineb Touati & Manuel Pereira & Rui Esteves Araújo & Adel Khedher, 2022. "Integration of Switched Reluctance Generator in a Wind Energy Conversion System: An Overview of the State of the Art and Challenges," Energies, MDPI, vol. 15(13), pages 1-25, June.
    5. Wanderson R. H. Araujo & Marcio R. C. Reis & Gabriel A. Wainer & Wesley P. Calixto, 2021. "Efficiency Enhancement of Switched Reluctance Generator Employing Optimized Control Associated with Tracking Technique," Energies, MDPI, vol. 14(24), pages 1-26, December.
    6. Wenjuan Hao & Gong Zhang & Wenbo Liu & Hui Liu & Yu Wang, 2022. "Methods for Reducing Cogging Force in Permanent Magnet Machines: A Review," Energies, MDPI, vol. 16(1), pages 1-27, 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:11:y:2018:i:11:p:3215-:d:184050. 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.