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Multiobjective Optimization of a Five-Phase Bearingless Permanent Magnet Motor Considering Winding Area

Zhou Shi, Xiaodong Sun, Gang Lei, Xiang Tian, Youguang Guo, Jianguo Zhu

2021IEEE/ASME Transactions on Mechatronics108 citationsDOI

Abstract

Due to the increasing demand for high-speed motors with high stability, bearingless motors have attracted much attention. Bearingless permanent magnet synchronous motors (BPMSMs) are a kind of motor, which uses suspension force to eliminate the motor bearings. This article proposes a five-phase BPMSM with 10 slots and 8 poles. Based on the principle of suspension force of BPMSM, an analytical expression of the suspension force is derived for the proposed BPMSM. To improve the suspension stability and torque, an optimization method consisting of a response surface model and a multiobjective optimization algorithm is employed. Not only the geometric parameters but also the winding distribution are considered in the optimization process. Finally, the effectiveness and superiority of the optimal design are verified by experiment.

Topics & Concepts

Suspension (topology)Control theory (sociology)MagnetTorqueMulti-objective optimizationStability (learning theory)Process (computing)Computer scienceEngineeringMathematicsMechanical engineeringPhysicsMachine learningOperating systemHomotopyThermodynamicsArtificial intelligencePure mathematicsControl (management)Magnetic Bearings and Levitation DynamicsElectric Motor Design and AnalysisSensorless Control of Electric Motors
Multiobjective Optimization of a Five-Phase Bearingless Permanent Magnet Motor Considering Winding Area | Litcius