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A Modified JAYA Algorithm for Optimization in Brushless DC Wheel Motor

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1159))

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Abstract

Brushless DC wheel motor has been widely used in various industrial fields and life, which has the advantages of high efficiency, light weight, speed range and so on. The parameters design of BLDC wheel motor is of great significance to its stability, efficiency and accuracy of motor operation. This paper proposes a modified JAYA (MJAYA) algorithm to optimize the parameters of the brushless DC wheel motor. In MJAYA, an experience-based learning strategy is proposed to improve the diversity of the population to avoid falling into the local optima. Experimental results show that the proposed MJAYA is feasible and effective in solving the parameters design problem of brushless DC wheel motor. In addition, MJAYA shows a superior performance compared with other commonly used algorithms.

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Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61673404, 61876169, 61976237), the Key Scientific Research Projects in Colleges and Universities of Henan Province (Grant No. 19A120014, 20A120013).

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Authors and Affiliations

  1. School of Electric and Information Engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China

    Li Yan, Chuang Zhang, Boyang Qu, Fangfang Bian & Chao Li

Authors
  1. Li Yan
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  2. Chuang Zhang
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  3. Boyang Qu
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  4. Fangfang Bian
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  5. Chao Li
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Corresponding author

Correspondence to Boyang Qu .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Yan, L., Zhang, C., Qu, B., Bian, F., Li, C. (2020). A Modified JAYA Algorithm for Optimization in Brushless DC Wheel Motor. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_53

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_53

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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