A Non-Permanent Magnet DC-Biased Vernier Reluctance Linear Machine with Non-Uniform Air Gap Structure for Ripple Reduction

Qiao, Zhenyang; Zhang, Yunpeng; Luo, Jian; Fu, Weinong; Shao, Dingguo; Cao, Huiming

doi:10.3390/act12010007

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The outer stator teeth serving as modulators have a flux modulation effect on the harmonics generated by NdFeB magnet excitation. The relative permeance functions of the modulator are governed by [24]…”

Section: Operating Principlementioning

confidence: 99%

Design and Analysis of a New Dual-Stator Hybrid Magnet Flux Modulation Machine

Meng,

Yang,

Wang

et al. 2024

Actuators

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This paper proposes a new dual-stator hybrid-magnet flux modulation machine (DS-FMHMM) for direct-drive applications, which employs NdFeB magnet excitation and Ferrite magnet excitation on the rotor and outer stator sides, respectively. With this design, the proposed DS-FMHMM can not only fully use the bidirectional flux modulation effect, but also effectively alleviate the magnetic saturation issue. The machine configuration is described, together with the operating principle. Then, the design parameters of DS-FMHMM are globally optimized for obtaining high torque quality, and the influence of magnet dimensions on torque is analyzed. To evaluate the merits of the proposed DS-FMHMM, the electromagnetic performances of machines under different magnet excitation sources are analyzed, and a comprehensive electromagnetic performance comparison of DS-FMHMM and two existing dual-stator flux modulation machines (DSFMMs) is developed.

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Section: Operating Principlementioning

confidence: 99%

Design and Analysis of a New Dual-Stator Hybrid Magnet Flux Modulation Machine

Meng,

Yang,

Wang

et al. 2024

Actuators

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Optimization Comparison of Torque Performance of Axial-Flux Permanent-Magnet Motor Using Differential Evolution and Cuckoo Search

Ge,

Xiao,

Cui

et al. 2024

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To improve the torque performance of the axial-flux permanent-magnet motor (AFPMM), differential evolution (DE) and cuckoo search (CS) are proposed for optimizing the motor’s structural parameters. The object of this research is an AFPMM with a single-rotor and double-stator configuration. Firstly, finite element analysis (FEA) and BP neural network machine learning (ML) were combined to obtain an ML calculator. This calculator is about the relationships between five input structural parameters of the motor and two output torque parameters (i.e., average torque and cogging torque). Then, an optimization objective function was designed to reduce the cogging torque while increasing the average output torque. And motor structural parameters were optimized using the DE and CS algorithms, respectively. Finally, air-gap flux density, average torque, cogging torque, and ripple torque before and after the optimization of the motor structure parameters are compared by FEA. The results show that both algorithms achieved almost the same optimized structural parameters. And the optimized motor has reduced cogging torque while increasing the average output torque and reducing the ripple torque. Compared with the CS, the DE is more advantageous in terms of faster iteration speed, shorter time to obtain the optimal solution, and less resource consumption.

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A Non-Permanent Magnet DC-Biased Vernier Reluctance Linear Machine with Non-Uniform Air Gap Structure for Ripple Reduction

Cited by 2 publications

References 13 publications

Design and Analysis of a New Dual-Stator Hybrid Magnet Flux Modulation Machine

Design and Analysis of a New Dual-Stator Hybrid Magnet Flux Modulation Machine

Optimization Comparison of Torque Performance of Axial-Flux Permanent-Magnet Motor Using Differential Evolution and Cuckoo Search

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