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A Novel Motor Structure with Extended Particle Swarm Optimization for Space Robot Control.
Gao, Hongwei; Liu, Zide; Wang, Xuna; Li, Dongyu; Zhang, Tian; Yu, Jiahui; Wang, Jianbin.
Afiliação
  • Gao H; School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110000, China.
  • Liu Z; School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110000, China.
  • Wang X; School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110000, China.
  • Li D; School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110000, China.
  • Zhang T; Beijing Bolean Intelligence Technology Co., Ltd., Beijing 100000, China.
  • Yu J; Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
  • Wang J; Ocean College, Zhejiang University, Hangzhou 316021, China.
Sensors (Basel) ; 23(8)2023 Apr 20.
Article em En | MEDLINE | ID: mdl-37112467
ABSTRACT
This paper studies motor structures and optimization methods for space robots, proposing an optimized stepped rotor bearingless switched reluctance motor (BLSRM) to solve the poor self-starting ability and significant torque fluctuation issues in traditional BLSRMs. Firstly, the advantages and disadvantages of the 12/14 hybrid stator pole type BLSRM were analyzed, and a stepped rotor BLSRM structure was designed. Secondly, the particle swarm optimization (PSO) algorithm was improved and combined with finite element analysis for motor structure parameter optimization. Subsequently, a performance analysis of the original and new motors was conducted using finite element analysis software, and the results showed that the stepped rotor BLSRM had an improved self-starting ability and significantly reduced torque fluctuation, verifying the effectiveness of the proposed motor structure and optimization method.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article