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Field Analysis and Flux-Weakening Control of PMSM Used in Vehicle

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Genetic and Evolutionary Computing (ICGEC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 834))

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Abstract

Permanent magnet synchronous motor (PMSM) is widely used in the electric vehicle industry due to its advantages of low noise, small volume, large power density, small moment of inertia, and high efficiency. A three-phase permanent magnet synchronous motor (PMSM) used in vehicle was designed in this paper. Using Ansoft Maxwell software the electromagnetic field of PMSM was analyzed by finite element method, and the conclusion of optimum design of vehicle motor was made. The paper also discussed how to meet the driving requirements of electric cars within the limit of vehicular power supply voltage and speed range by using the method of flux-weakening control.

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Acknowledgements

This research was supported by the Science and Technology Project Fund of Fuzhou Science and Technology Bureau (Grant No. 2016-G-57).

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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

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

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Editors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Department of Computing, Mathematics, and Physics, Western Norway University of Applied Sciences, Bergen, China

    Jerry Chun-Wei Lin

  3. Changzhou College of Information Technology, Changzhou, Jiangsu, China

    Bixia Sui

  4. College of Smart Living and Management, Tajen University, Pingtung, Taiwan

    Shih-Pang Tseng

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Liu, ZS. (2019). Field Analysis and Flux-Weakening Control of PMSM Used in Vehicle. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_37

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