Modelling and optimization for a special pole bearingless induction motor

ABSTRACT

A special pole bearingless induction motor (SPBIM) with improved rotor structure is proposed, which shields the interference of suspension winding to torque. To achieve the optimal performance of the SPBIM, a multi-objective optimization design is proposed based on a bi-level optimization scheme. The basic structure and mathematical model of SPBIM are presented and analysed. Then, the optimized parameters are stratified into sensitive and sub-sensitive parameters. For sensitive parameters, the artificial fish swarm algorithm based on the fitting function from the response surface method is adopted. For sub-sensitive parameters, the multi-objective random search method, based on the finite element method (FEM), is used, and the final optimal solution is obtained. Based on the optimized parameters and optimal solution, the suspension and driving performance between the initial and optimal SPBIM are compared using the FEM. Finally, the optimal prototype is manufactured. The experimental results confirm the effectiveness of the motor design and optimization scheme.

KEYWORDS:

• Special pole bearingless induction motor (SPBIM)
• multi-objective optimization
• suspension force
• torque

Acknowledgements

This work was supported by the Natural Science Foundation of China (51875261), the Natural Science Foundation of Jiangsu Province of China (BK20221366), the Doctoral Research and Innovation Project of Jiangsu Province (KYCX21_3362) and the Priority Academic Program Development of Jiangsu Higher Education Institution.

Availability of data

The authors confirm that the data supporting the findings of this study are available within the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 51875261]; Natural Science Foundation of Jiangsu Province [grant number BK20221366]; Doctoral Research and Innovation Project of Jiangsu Province [grant number KYCX21_3362].