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Energies
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Optimization and Simulation of Permanent Magnet Motors
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Optimization and Simulation of Permanent Magnet Motors

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (10 May 2022) | Viewed by 7198

Special Issue Editors

Prof. Dr. Damir Žarko

E-Mail Website
Guest Editor
Department of Electric Machines, Drives and Automation, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Interests: electric machines and drives for power systems, electromobility, aerospace and general industrial applications; design, simulation and optimization of electric machines and power transformers
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ayman EL-Refaie

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI 53233, USA
Interests: electrical machines and drives; transportation electrification; renewable energies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electric machines are the main workhorses of our modern world. Among them, permanent magnet (PM) machines have reserved a special place for applications where high efficiency combined with high torque density and reduced size and weight are important. High-performance applications often require the electric machine to fulfill several conflicting requirements, thus pushing its design electromagnetically, thermally, and mechanically to the edge of feasibility. In such cases, machine designers face a serious challenge and need to resort to reliable multiphysical models combined with mathematical optimization as an automated decision-making tool.

This Special Issue focuses on simulation and optimization of permanent magnet machines used as a design tool. The specific topics of interest include (but are not limited to) the following:

  • Analytical, semi-analytical, and numerical models;
  • Electromagnetic, thermal, mechanical, and multiphysical models;
  • Advanced iron loss and winding loss models;
  • Simulation model tuning based on testbench measured data;
  • Deterministic, heuristic or meta-model based single-objective and multiobjective optimization of PM machines;
  • Reduction of computation efforts in optimization of PM machines using time-efficient preparation and solving of machine models and/or parallelization of the optimization tasks;
  • Introduction of improved or novel optimization methods applied to PM machine design;
  • Application-targeted (aerospace, traction, high-speed, etc.) simulation and optimization.

Prof. Dr. Damir Žarko
Prof. Dr. Ayman EL-Refaie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Permanent magnet machines
  • Modeling
  • Multiphysics
  • Heuristic optimization
  • Meta-model based optimization
  • Single- and multiobjective optimization
  • Parallel computing in optimization
  • Computation time minimization

Published Papers (4 papers)

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Research

24 pages, 5158 KiB  
Article
Comparison between Space Mapping and Direct FEA Optimizations for the Design of Halbach Array PM Motor
by Ramón Pérez, Alexandre Pelletier, Jean-Michel Grenier, Jérôme Cros, David Rancourt and Richard Freer
Energies 2022, 15(11), 3969; https://doi.org/10.3390/en15113969 - 27 May 2022
Cited by 3 | Viewed by 1422
Abstract
Effective methods for the design of high-performance electrical machines must use optimization techniques and precise and fast physical models. Convergence, precision and speed of execution are important issues, in addition to the ability to explore the entire domain of solutions. The finite element [...] Read more.
Effective methods for the design of high-performance electrical machines must use optimization techniques and precise and fast physical models. Convergence, precision and speed of execution are important issues, in addition to the ability to explore the entire domain of solutions. The finite element method (FEM) presents a high accuracy in the results but with high computational costs. Analytical models, on the other hand, solve the problem quickly but compromise the accuracy of the results. This work shows a comparison between an optimization made with an analytical electromagnetic model and a direct optimization with finite element field calculation for the optimal design of a Halbach array permanent magnet synchronous motor (PMSM). In the case of the analytical model, it is necessary to use an iterative method of correcting the model to obtain a valid solution. This method is known as Space Mapping (SM) and the analytical model can be improved with a reduced number of iterations with the FEM. The results show a rapid convergence towards an optimal solution for the SM, with more than 78% reduction in computational cost compared to a Direct FEM optimization. Both solutions have only a difference of 3% on the power density, which indicates that FEM does not improve the results obtained by SM. This represents a great advantage that allows for the consideration of a large amount of designs to analyze the domain of solutions in more detail. This study also shows that SM is a powerful method to optimize the power density or torque density of electrical machines. Full article
(This article belongs to the Special Issue Optimization and Simulation of Permanent Magnet Motors)
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18 pages, 2253 KiB  
Article
Torque Ripple Minimizing of Uniform Slot Machines with Delta Rotor via Subdomain Analysis
by Minhyeok Lee, Yunkyung Hwang and Kwanghee Nam
Energies 2021, 14(21), 7390; https://doi.org/10.3390/en14217390 - 5 Nov 2021
Cited by 2 | Viewed by 1545
Abstract
Since the slot opening is large in the uniform slot machine, the torque ripple generated by overlapping or misaligning with the rotor cavity is remarkably large in the case of interior permanent magnet (IPM) machine. In this work, it is observed that the [...] Read more.
Since the slot opening is large in the uniform slot machine, the torque ripple generated by overlapping or misaligning with the rotor cavity is remarkably large in the case of interior permanent magnet (IPM) machine. In this work, it is observed that the magnitude of torque ripple depends strongly on the phase difference between air-gap field harmonics: The ripple is minimized when the two dominant harmonic components cancel each other. Based on this fact, a condition is developed to minimize torque ripple by adjusting the q-flux channel width and d-flux barrier width. The torque ripple minimizing solution is found from a level chart made by subdomain time-stepping analysis. Finite element analysis (FEA) also gives a very similar minimizing solution. A prototype machine is manufactured, and its performances are validated through experiments. Full article
(This article belongs to the Special Issue Optimization and Simulation of Permanent Magnet Motors)
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13 pages, 4748 KiB  
Article
Comparative Study of Stepwise Optimization and Global Optimization on a Nine-Phase Flux-Switching PM Generator
by Feng Li and Xiaoyong Zhu
Energies 2021, 14(16), 4754; https://doi.org/10.3390/en14164754 - 5 Aug 2021
Cited by 3 | Viewed by 1314
Abstract
In this paper, the design procedure and optimization process of a multi-phase flux-switching permanent magnet (FSPM) generator for wind power generation system is investigated. Two different optimization methods—stepwise optimization and global optimization—are implemented and applied to the optimization of the proposed nine-phase FSPM [...] Read more.
In this paper, the design procedure and optimization process of a multi-phase flux-switching permanent magnet (FSPM) generator for wind power generation system is investigated. Two different optimization methods—stepwise optimization and global optimization—are implemented and applied to the optimization of the proposed nine-phase FSPM generator-based wind power system. Both the advantages and disadvantages of two optimization methods are compared and analyzed. The results indicate that the stepwise optimization can achieve good effects on individual optimization objectives, whereas the global optimization can not only achieve a good optimization effect on a single objective, but also can find design point on the Pareto front, which can effectively optimize different multi-objects. The electromagnetic performance of the nine-phase FSPM generator is verified by experiments on a prototyped machine and the measured results show that the proposed generator exhibits the favorable characteristics of high torque, low torque ripple, and high efficiency. Full article
(This article belongs to the Special Issue Optimization and Simulation of Permanent Magnet Motors)
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16 pages, 1210 KiB  
Article
Minimum Set of Rotor Parameters for Synchronous Reluctance Machine and Improved Optimization Convergence via Forced Rotor Barrier Feasibility
by Branko Ban, Stjepan Stipetic and Tino Jercic
Energies 2021, 14(10), 2744; https://doi.org/10.3390/en14102744 - 11 May 2021
Cited by 8 | Viewed by 1969
Abstract
Although rare earth materials are the critical component in high torque density permanent magnet machines, their use has historically been a commercial risk. The alternatives that have been in the recent industry focus are synchronous reluctance machines (SyRM). They have lower torque density [...] Read more.
Although rare earth materials are the critical component in high torque density permanent magnet machines, their use has historically been a commercial risk. The alternatives that have been in the recent industry focus are synchronous reluctance machines (SyRM). They have lower torque density but also relatively low material cost and higher overload capability. Multi-layer IPM and SyRM machines have significant geometric complexity, resulting in a high number of parameters. Considering that modern machine design requires the use of optimization algorithms with computational load proportional to the number of parameters, the whole design process can take several days. This paper presents novel SyRM parameterization with reduced number of parameters. Furthermore, the paper introduces the novel forced feasibility concept, applied on rotor barrier parameters, resulting in improved optimization convergence with overall optimization time reduced by 12.3%. Proposed approaches were demonstrated using optimization procedure based on the existing differential evolution algorithm (DE) framework. Full article
(This article belongs to the Special Issue Optimization and Simulation of Permanent Magnet Motors)
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