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A novel bearingless segmented switched reluctance motor (BSSRM) is proposed in this paper to solve the coupling problem of the traditional bearingless switched reluctance motor (BSRM). Different from traditional BSRMs, the proposed BSSRM adopts the double stator and segmented rotor structure, thereby making the motor operate in short flux paths and the magnetic flux path isolated between torque and suspension system. On the basis of introducing the structure and working principle of the BSSRM, the mathematical model of torque and suspension force is deduced. The 2D finite element simulation model is established by the Ansoft software. The influence of structural parameters on torque and suspension system is analyzed, and its electromagnetic characteristic and decoupling characteristic are analyzed. Compared with the double stator bearingless switched reluctance motor (DSBSRM), the BSSRM not only improves the torque and suspension output but also weakens the coupling between torque and suspension system. Finally, the simulation results verify the effectiveness of the BSSRM. INDEX TERMSBearingless switched reluctance motor, segmented rotor, decoupling characteristic, electromagnetic characteristic.

The vibration and noise problems caused by the radial electromagnetic force of the Bearingless Switched Reluctance Motor (BSRM) severely restrict its wide application. The purpose of this paper is to research the electromagnetic vibration and noise of Single-Winding Bearingless Switched Reluctance Machine (SWBSRM). Firstly, the radial electromagnetic force, which is the excitation source of electromagnetic vibration, is analyzed. Secondly, the three-dimensional (3D) model of stator structure is established by ANSYS finite element analysis (FEA) software, and its modal analysis is carried out to obtain its modal shape and corresponding modal frequency, which provides a reference and basis for researching the mechanical vibration of the SWBSRM. Finally, the harmonic response field analysis and sound field analysis model are established, and the vibration and noise of the motor under radial electromagnetic force are analyzed by using the magnetic-solid weak coupling analysis method.

Optimization design is a satisfactory way to improve the performance of magnetic bearing (MB). In this paper, a multi-objective genetic algorithm of particle swarm optimization (GAPSO) is proposed for homopolar permanent magnet biased magnetic bearings (HPRMBs). By assigning different inertia weights to each objective function, the multi-objective function is transformed into a new single objective function for optimization. In order to ensure the diversity of particles in the optimization process, genetic algorithm is used to cross-mutate them, which enhances the global search ability of particle swarm optimization. After optimization with GAPSO, the levitating force of the MB is increased by 22.3%, the volume decreased by 26.6%, and the loss reduced by 33.9%. The optimization results show that the multi-objective optimization based on GAPSO can effectively improve the performance of HPRMB.