Machines (Jul 2022)

Sensitivity Analysis for Multi-Objective Optimization of Switched Reluctance Motors

  • Ekaterina Andriushchenko,
  • Ants Kallaste,
  • Mohammad Hossain Mohammadi,
  • David A. Lowther,
  • Hamidreza Heidari

DOI
https://doi.org/10.3390/machines10070559
Journal volume & issue
Vol. 10, no. 7
p. 559

Abstract

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The main issue of the switched reluctance motor (SRM) is its noise and vibration caused by high torque ripples on the rotor’s shaft. Many methods have been developed for improving the torque characteristic of the SRM. For example, design optimization is one of the promising approaches to the noise and vibration reduction of the SRM. Particularly, topology optimization (TO) of the stator and rotor can be highly beneficial to addressing the torque ripple issue. However, the TO of the SRM appears to be computationally demanding. To overcome this issue, this study proposes a method aiming to reduce the computational complexity of the TO through the reduction of the design space. Particularly, this paper presents a sensitivity analysis of a list of unique design parameters of the SRM and their influence on the average torque of the motor and the torque ripple of the motor. By applying the sensitivity analysis, the design space of the TO could be reduced, leading to a considerable decrease in the TO computational burden. Additionally, valuable conclusions on the geometrical parameters’ influences on the SRM torque and torque ripple have been drawn.

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