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Design and Performance Simulation of Direct Drive Hub Motor Based on Improved Genetic Algorithm

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Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 682))

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Abstract

By using improved genetic algorithm (IGA), a direct drive hub motor with high efficiency and low-cost was designed. According to the characteristics of the hub motor, a mathematical model for optimize of direct drive hub motor was established, and optimized calculation was extended, and finally a prototype was developed. The simulation results show that the novel direct-drive hub motor can meet the requirements of great torque when low speed and high speed when constant power, so it is very suitable for the vehicle.

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Acknowledgment

This research was supported by the Natural Science Foundation of Fujian Province of China. (Grant No. 2017J01667).

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Authors and Affiliations

  1. School of Information Science and Engineering, Fujian University of Technology, Fuzhou, 350118, China

    Zhong-Shu Liu

  2. The Key Laboratory for Automotive Electronics and Electric Drive of Fujian Province, Fujian University of Technology, Fuzhou, 350118, China

    Zhong-Shu Liu

Authors
  1. Zhong-Shu Liu
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Correspondence to Zhong-Shu Liu .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VÅ B-Technical University of Ostrava , Ostrava-Poruba, Czech Republic

    Pavel Krömer

  2. Dept. Lenguajes y Ciencias de la Computación, University of Málaga, Málaga, Spain

    Enrique Alba

  3. Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  4. Department of Computer Science, VÅ B-Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

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Liu, ZS. (2018). Design and Performance Simulation of Direct Drive Hub Motor Based on Improved Genetic Algorithm. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_33

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  • DOI: https://doi.org/10.1007/978-3-319-68527-4_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68526-7

  • Online ISBN: 978-3-319-68527-4

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