Multi Objective Optimization Design of Unequal Halbach Array Permanent Magnet Vernier Motor Based on Optimization Algorithm

Chen, Qiushuo; Fan, Ying; Lei, Yutong; Wang, Xu

doi:10.1109/ecce47101.2021.9595558

Cited by 5 publications

(4 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, even though there are challenges in the manufacture of such Halbach arrangements, three-segment HAVMs are manufactured in [26] and HAs with four-segment structure are manufactured in [27] for a linear VM. Hence, with careful design, the manufacture of five-segment HA is also possible.…”

Section: Discussionmentioning

confidence: 99%

High-Performance Vernier Machines with Halbach Array Permanent Magnets for Direct Drive Applications

2023

View full text Add to dashboard Cite

This paper investigates the performance enhancements of permanent magnet Vernier machines (PMVMs) that can be achieved using a new structure of Halbach array permanent magnets (HAPMs) for a direct-drive motorcycle application. To start with, size and design specifications of the electric machine are determined based on the assumed acceleration and drive cycle performance of a motorcycle. Then, five-segment Halbach array permanent magnet Vernier machines (HAPMVMs) with two different slot/pole combinations (24 s/44 p and 12 s/20 p) are suggested and optimized to achieve a high torque density with an acceptable power factor while maintaining a low torque ripple. Two selected designs from optimizations are investigated in the full speed range considering power factor and efficiency maps. Consequently, in order to demonstrate the effectiveness of the proposed five-HAPM structure, the same optimization methods are repeated with three-segment HAPMs as well as with single-piece PMs. The comparisons show a great enhancement in torque and power factor achieved with the use of five HAPMs. For instance, for 22 s/44 p topology, generated torque doubles with the use of five-segment PMs compared to single-segment PMs. Finally, the harmonics of magnetic flux density in the airgap of PMVMs and HAPMVMs are compared and investigated to reveal the reasons behind the superiority of VMs with HAPMs.

show abstract

Section: Discussionmentioning

confidence: 99%

High-Performance Vernier Machines with Halbach Array Permanent Magnets for Direct Drive Applications

2023

View full text Add to dashboard Cite

show abstract

“…Based on the screening results, 77 RSM test spaces are established as shown in Table 3. After the experimental design space is established using RSM [12,13]. It can also efficiently build polynomial regression models to fit the relationship among thrust force, thrust fluctuation, and parameters, which can be expressed as follows:…”

Section: Establishment Of Regression Modelmentioning

confidence: 99%

Co-optimization of Long Secondary Double-sided Linear Flux Switching Permanent Magnet Motors

Wen,

Cui,

et al. 2024

PIER C

View full text Add to dashboard Cite

This study aims to achieve the co-optimization of thrust force and thrust fluctuation using a long secondary double-sided linear flux switching permanent magnet motor (LSDLFSPM). Firstly, the motor model is constructed and derived using a theoretical approach. Subsequently, the motor parameters are subjected to sensitivity analysis using the Taguchi method to identify the significant influencing factors. Based on the screening results, the Response Surface Method (RSM) is employed to construct the test space and derive regression equations for thrust force and thrust fluctuation. The Multi-Objective Grasshopper Optimization Algorithm (MOGOA) is then utilized to iteratively optimize the regression equation for optimal parameter sizes. Finally, the optimized results are validated through finite element analysis (FEA) and compared with the original motor performance to demonstrate the effectiveness of the optimization approach proposed in this paper.

show abstract

“…The solutions obtained in these ways are closely related to the defined weights and have high subjectivity. To address the issues raised above, references [22][23][24] adopted multi-objective particle swarm optimization (MOPSO) based on Pareto optimal sequencing. Although they proposed various MOPSO improvement strategies, finding a globally optimal solution is still challenging since diversity and convergence are tricky to balance.…”

Section: Introductionmentioning

confidence: 99%

Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

Wang,

Pan,

Niu

2023

CMC

View full text Add to dashboard Cite

The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of the complex input-output relationship and the strong nonlinearity of PMEC. Then, a novel competition mechanism-based multi-objective particle swarm optimization algorithm (NCMOPSO) is proposed to find the optimal structural parameters of PMEC. Chaotic search and mutation strategies are used to improve the original algorithm, which improves the shortcomings of multi-objective particle swarm optimization (MOPSO), which is too fast to converge into a global optimum, and balances the convergence and diversity of the algorithm. In order to verify the superiority and applicability of the proposed algorithm, it is compared with several popular multi-objective optimization algorithms. Applying them to the optimization model of PMEC, the results show that the proposed algorithm has better comprehensive performance. Finally, a finite element simulation model is established using the optimal structural parameters obtained by the proposed algorithm to verify the optimization results. Compared with the prototype, the optimized PMEC has reduced eddy current losses by 1.7812 kW, increased output torque by 658.5 N•m, and decreased costs by 13%, improving energy transfer efficiency.

show abstract

Multi Objective Optimization Design of Unequal Halbach Array Permanent Magnet Vernier Motor Based on Optimization Algorithm

Cited by 5 publications

References 14 publications

High-Performance Vernier Machines with Halbach Array Permanent Magnets for Direct Drive Applications

High-Performance Vernier Machines with Halbach Array Permanent Magnets for Direct Drive Applications

Co-optimization of Long Secondary Double-sided Linear Flux Switching Permanent Magnet Motors

Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

Contact Info

Product

Resources

About