Multi-Objective Optimal Design of Permanent Magnet Synchronous Motor for High Efficiency and High Dynamic Performance

Research output: Contribution to journalArticlepeer-review

Abstract

There is a strong demand for the research of electric vehicles (EVs) in automotive industry, because of an increased concern of the energy depletion and environmental pollution problems caused by oil-fueled automotive. The traction motor drive system is one of the core components of EVs, and a motor with superior dynamic performance and high efficiency could significantly reduce energy consumption and improve riding comfort of EVs. Therefore, in order to achieve high dynamic performance and high efficiency of permanent magnet synchronous motor (PMSM), a multi-objective optimization design method for PMSM based on the artificial bee colony algorithm was proposed in this paper. First, based on the magnetic field analytical model of PMSM, the analytical expressions of the key parameters were deduced, namely, mechanical time constant and electrical time constant. Second, the efficiency and electrical and mechanical time constant were defined as optimization objectives. Third, the efficiency and dynamic performance of the original motor and optimized motor were compared applying the finite-element analysis. Furthermore, one prototype machine was manufactured according to the results of optimization. The dynamic performance and efficiency of the prototype had been tested. The experiments show confident results that the efficiency increased about 1% and the mechanical time constant reduced to 31.4% of initial value.

Original languageEnglish
Pages (from-to)23568-23581
Number of pages14
JournalIEEE Access
Volume6
DOIs
StatePublished - 19 Apr 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Parameter sensitivity
  • artificial bee colony algorithm
  • dynamic performance
  • efficiency

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