4.6 Article

Robust Design Optimization of a Five-Phase PM Hub Motor for Fault-Tolerant Operation Based on Taguchi Method

Journal

IEEE TRANSACTIONS ON ENERGY CONVERSION
Volume 35, Issue 4, Pages 2036-2044

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEC.2020.2989438

Keywords

Permanent magnet motors; Synchronous motors; Optimization; Circuit faults; Fault tolerance; Fault tolerant systems; Torque; Permanent-magnet synchronous hub motors; manufacturing tolerances; robust design; Taguchi method; fault-tolerant operation

Funding

  1. National Natural Science Foundation of China [51875261, 51875255]
  2. National Key Research and Development Program of China [2017YFB0102603]
  3. Natural Science Foundation of Jiangsu Province of China [BK20180046, BK20170071, BK20180100]
  4. Qinglan Project of Jiangsu Province
  5. Natural Science Foundation of Jiangsu Higher Education Institutions [17KJA460005]
  6. Six Categories Talent Peak of Jiangsu Province [2015-XNYQC-003, 2018-TD-GDZB-022]
  7. Key Project for the Development of Strategic Emerging Industries of Jiangsu Province [2016-1094]
  8. Postgraduate Research & the Practice Innovation Program of Jiangsu Province [KYCX17_1815]
  9. State Scholarship Fund of China Scholarship Council [201908320298, TEC-00048-2020]

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This article investigates the efficient robust design optimization of a five-phase permanent magnet (PM) hub motor for electric vehicles. Besides the requirement of high-performance, like high torque density, low torque ripple and efficiency, fault-tolerant operation capability are also considered in the design optimization. To ensure that the motor performance is not sensitive to the variations of manufacturing tolerances, robust design optimization is employed to the investigated motor. To improve the fault tolerant capability of the motor, the motor performances under fault operation are also considered in the optimization. A Fuzzy-based sequential Taguchi robust optimization method is proposed to improve the comprehensive performance and save computing time. The proposed method is efficient because it holds the advantages of Taguchi method, fuzzy theory, and sequential optimization strategy. The motor performance is improved significantly by using the proposed method. Experimental results verify the accuracy of the model used in this study.

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