Design and Optimization of a Dual-Permanent-Magnet Vernier Machine With a Novel Optimization Model

Lin, Qifang; Niu, Shuangxia; Fu, Weinong

doi:10.1109/tmag.2019.2956071

Cited by 19 publications

(7 citation statements)

References 13 publications

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“…In [20], a design method of the vernier machine with dual PM was proposed. And [21] also revealed that the dual PM vernier machine has a better performance than stator-PM and rotor-PM machines. In [22], several dual-PM-excited motors have different stator structures with the same rotor are comparatively studied.…”

Section: Introductionmentioning

confidence: 93%

Comparative Analysis of Different Permanent Magnet Arrangements in a Novel Flux Modulated Electric Machine

Huang

Niu

et al. 2021

IEEE Access

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A novel dual permanent magnet (PM) machine with Halbach segmentation flux modulation is proposed in this paper, which is evolved from a flux switching PM machine (FSPM). In order to improve the performance of the FSPM, several PM arrangement methods have been adopted and three new different structures have been investigated. To achieve a fair comparison, all the structures are under the same size and rotate at the same speed. The performances of output torque and back EMF are compared. The analysis results show that the dual PM with Halbach segmentation has the highest torque density and power efficiency. The torque is improved by 100.3% from the FSPM while the PM volume does not increase too much. The unique of this best structure is that it not only combines the vernier machine and FSPM machine together, but also reduces the torque ripple. The performance of the motor is verified by the simulation using finite-element analysis (FEA).

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Section: Introductionmentioning

confidence: 93%

Comparative Analysis of Different Permanent Magnet Arrangements in a Novel Flux Modulated Electric Machine

Huang

Niu

et al. 2021

IEEE Access

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“…The rest of the machine parameters are unchanged as listed in Table 1 while the winding configuration applied has the winding function harmonics listed in row 2 of Table 2. With the new number of magnet and stator poles, the Vernier effect is satisfied and hence the machine is classified as a Vernier machine [35]- [38].…”

Section: -D Fea Validation With Non-sinusoidal Back-emfmentioning

confidence: 99%

Novel ABC—Variable Based Closed-Form Analytical Model of Surface Mounted Permanent Magnet AC Machines With Sinusoidal and Non-Sinusoidal Back-EMF

2022

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This work presents a novel abc-based model applicable to surface-mounted permanent magnet AC (SM-PMAC) machines with sinusoidal and non-sinusoidal back-emf. It is capable of predicting the electromagnetic performance metrics such as torque waveforms, machine inductances, flux linkages and back-emf. The closed form expressions of the model, which can be evaluated with a high computational efficiency, are derived from basic geometric and winding parameters. Validation of the model is carried out numerically and experimentally with a very good match in results. Finally, the computational efficiency of the model is highlighted by considering a multi-objective evolutionary optimization design of SM-PMAC machine with a relatively large number of design parameters, where results are presented and discussed.

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“…Among the modern optimization methods, genetic algorithm (GA) is most commonly used in optimizing VMs for its superior advantage in global searching [12,13]. In [14], Lin et al proposed the numerical presentations for the design configurations of a DPMVM and optimized the numerical sets through GA. Wang et al [15] investigated the influences of the structural parameters of an axial-flux PMVM on the output torque and axial electromagnetic force. A Kriging prediction method was utilized to model the influences, and GA was combined with the prediction model to search for an optimized result.…”

Section: State-of-the-artmentioning

confidence: 99%

A Taguchi-preconditioned GA Method for the Design Optimization of a PM Vernier Motor

Zhu¹,

Liu²,

Li³

et al. 2022

PIER C

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This paper presents an efficient Taguchi-preconditioned genetic algorithm (TPGA) strategy for the design optimization of a 630-kW permanent magnet vernier motor (PMVM). In the TPGA, firstly, the Taguchi method is combined with comparative finite element analyses (FEA) to judge the influence factors of six typical structural parameters on the torque output. Secondly, four influential parameters are taken from the six typical ones and decided as the variables in the global optimization processes coupling genetic algorithm (GA) and FEA. As two variables with small influence factors are set to constants in the computationally costly optimization processes, the calculation burden can thus be effectively reduced. Thirdly, with the four influential optimization variables, FEA-assisted GA is used to maximize the output torque of the PMVM. During the global optimization processes, a preliminarily optimized structural configuration obtained from the Taguchi analyses is used as the initial values of the variables. Finally, the working performances of the machine with the optimal parameters are obtained through FEM calculations. The optimization effectiveness is validated by comparing the output torque of the GA-optimized machine with that of the initial and the Taguchi-preliminary optimized ones.

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Design and Optimization of a Dual-Permanent-Magnet Vernier Machine With a Novel Optimization Model

Cited by 19 publications

References 13 publications

Comparative Analysis of Different Permanent Magnet Arrangements in a Novel Flux Modulated Electric Machine

Comparative Analysis of Different Permanent Magnet Arrangements in a Novel Flux Modulated Electric Machine

Novel ABC—Variable Based Closed-Form Analytical Model of Surface Mounted Permanent Magnet AC Machines With Sinusoidal and Non-Sinusoidal Back-EMF

A Taguchi-preconditioned GA Method for the Design Optimization of a PM Vernier Motor

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