Optimization of Permanent Magnet Machines using Analytical Sub-Domain Model and Differential Evolution Algorithm

  • Abstract
  • Keywords
  • References
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  • Abstract

    This paper presents an optimization of permanent magnet synchronous machines (PMSMs) using Analytical Sub-domain Model together with Differential Evolution Algorithm (ASDEA). A three-phase, 6-slot/4-pole, surface-mounted PMSM is selected in the design with initial motor parameters which are determined from the sizing equations. Five motor parameters are to be optimized i.e. magnet thickness, airgap length, slot-opening width, magnet arc, and stator inner radius. Four objective functions are chosen i.e. to have lowest total harmonic distortions in the induced back-emf, lowest cogging torque, highest output torque and highest efficiency. Results show a good agreement between the analytical method and finite element analysis (FEA). The optimization of 6-slot/4-pole PMSM is further analyzed by comparing with other optimization algorithms i.e. Analytical Sub-domain with Genetic Algorithm (ASGA), and Analytical Sub-domain with Particle Swarm Optimization (ASPSO). It is observed that ASPSO has the fastest computing time compared to ASGA and ASDEA. Whereas ASDEA is approximately 50% faster than ASGA. The design work for PMSMs can potentially become faster without compromising the accuracy. While repetitive changes in motor parameters in finite element modeling could be avoided after applying this Analytical Sub-domain with Differential Evolution Algorithm.




  • Keywords

    analytical sub-domain; differential evolution; permanent magnet synchronous machines; back-emf; cogging torque.

  • References

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Article ID: 24418
DOI: 10.14419/ijet.v7i4.40.24418

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