Slotless tubular PM generator with dual quasi‐Halbach magnetized PM Array: Analytical and numerical magnetic field analysis

CheshmehBeigi, Hassan Moradi

doi:10.1002/jnm.2569

Cited by 1 publication

(1 citation statement)

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“…Reference [17] proposed a configuration of the study that utilizes an assisted dc field coil replaced with the permanent-magnet excitation, which efficiently improves the magnetic performance by reducing the reluctance and leakage flux. Reference [18] proposed an initial design and analytical electromagnetic field solution for the Slotless and Dual Quasi-Halbach Permanent Magnet mover. The obtained results from finite-element method analysis and analytical magnetic field solution show an enhancement in the proposed alternator performance compared with the alternator with Halbach magnetized configuration, by improving the provided power.…”

Section: Introductionmentioning

confidence: 99%

Torque ripple reduction of brushless DC motor with convex arc‐type permanent magnets based on robust optimization design

Feng

Zhang

Wei

et al. 2022

IET Electric Power Appl

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The mass production of the motors causes tolerance of shape and dimension, deviation of permanent magnet remanence and rotor eccentricity error, which affect the cogging torque and torque ripple amplitude and performance consistency. In order to reduce the torque ripple of the motor in the actual condition, the robustness optimization is performed in the paper. Firstly, an improving convex arc type permanent magnet structure is adopted to improve air gap flux density and suppress the cogging torque. Secondly, the structure parameters of the magnetic pole are selected as optimization variables, and the magnetization angle, remanence and position of the permanent magnet, static and dynamic rotor eccentricity are considered as noise factors. To improve the overall robustness of the motor under different operating conditions, the dynamic Taguchi method is used to optimize the robustness of the motor, and the test data is processed through the relation analysis method to obtain the optimal combination of control factors. Finally, the prototype is manufactured for the experiment. Compared with the single-operating conditions robust optimization results, the robust optimization method improves the robustness of the motor. The cogging torque amplitude is reduced by 39.2%. The torque ripple is 38.4% lower than that before optimization.

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Section: Introductionmentioning

confidence: 99%