Rotor Multidisciplinary Optimization of High Speed PMSM Based on Multi-Fidelity Surrogate Model and Gradient Sequential Sampling

Xie, Bingchuan; Zhang, Yue; Xu, Zhenyao; Zhang, Fengge

doi:10.1109/tec.2022.3214992

Cited by 4 publications

(11 citation statements)

References 25 publications

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“…A similar approach is employed in [72]. The method described in [73] is comparable but incorporates a MEC for achieving a low fidelity and low computational effort. In [64], all three fidelity levels are combined.…”

Section: Electromagnetic Domainmentioning

confidence: 99%

“…The contact pressure, the thermal expansion as well as the centrifugal forces are considered. Similar approaches to design rotor magnets and rotor sleeves are adopted in [8,39,55,73,75]. Some authors use analytical calculations for more detailed rotor and stator geometries as well, e.g., ribs in SynRM rotors by employing beam theory simplifications [36].…”

Section: Structural Mechanicsmentioning

confidence: 99%

“…Reference [69] uses an analytical estimation of the critical speed based on a simplified rotor geometry. Reference [73] uses a lumped-parameter model by dividing the rotor into disk segments, allowing the incorporation of multiple diameters and material properties. Some authors make use of higher fidelity analyses for the rotordynamics analyses.…”

Section: Rotordynamicsmentioning

confidence: 99%

“…Reference [92] uses a similar approach. A few authors use a campbell diagram for the analysis and visualization of critical speed ranges [73,96].…”

Section: Rotordynamicsmentioning

confidence: 99%

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Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework

Umland,

Winkler,

Inkermann

2023

Energies

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Electric motor development is a challenging task, as higher efficiency requirements and various interdependencies between different engineering domains must be considered. Established design approaches often lack the ability to address these interdependencies because they focus on specific domains and properties. Automated, multidisciplinary design approaches hold untapped potential for optimizing motors in terms of diverse requirements and advancing the development of more efficient and reliable motors. This paper presents a systematic literature review of the current state of research in the multidisciplinary design automation of electric motors. The literature basis comprises 1005 publications that are identified by a systematic internet search. The review of the existing approaches is based on twelve criteria that characterize the design automation task in general, such as knowledge representation or reasoning methods used, as well as criteria specific to electric motor design, such as domains considered and their coupling. The analysis reveals what current approaches are lacking: Consequent analysis and integration of domains, applicability of suggested methods, incorporation of established multidisciplinary design optimization (MDO) architectures, alongside the consideration of passive components in the motor. Aside from the introduction of twelve criteria for systematic charaterization of multidisciplinary design automation of electric motors, this article expands the state of the art by proposing an initial framework to establish process chains tackling the identified gaps in the review.

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Section: Electromagnetic Domainmentioning

confidence: 99%

Section: Structural Mechanicsmentioning

confidence: 99%

Section: Rotordynamicsmentioning

confidence: 99%

“…Reference [92] uses a similar approach. A few authors use a campbell diagram for the analysis and visualization of critical speed ranges [73,96].…”

Section: Rotordynamicsmentioning

confidence: 99%

See 2 more Smart Citations

Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework

Umland,

Winkler,

Inkermann

2023

Energies

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“…While the accuracy of finite element simulation has gained wide acceptance in the industrial domain, its intensive computational time significantly hampers optimization efficiency. Consequently, surrogate models have garnered attention in the optimization domain due to their lower computational time costs [1]. Presently, they find extensive application in structural optimization design [2] [3], aerodynamic optimization design [4] [5], multidisciplinary optimization [6], among other areas.…”

Section: Introductionmentioning

confidence: 99%

A Mixed-Variable Experimental Design Method

Wan,

Wang

2024

OJAppS

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Mixed-variable problems are inevitable in engineering. However, few researches pay attention to discrete variables. This paper proposed a mixed-variable experimental design method (ODCD): first, the design variables were divided into discrete variables and continuous variables; then, the DVD method was employed for handling discrete variables, the LHD method was applied for continuous variables, and finally, a Columnwise-Pairwise Algorithm was used for the overall optimization of the design matrix. Experimental results demonstrated that the ODCD method outperforms in terms of the sample space coverage performance.

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Optimization Design of Dual‐Parallel Rotor Permanent Magnet Motor Based on Dynamic Kriging Surrogate Model

Chen,

Tao,

et al. 2024

IEEJ Transactions Elec Engng

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In order to reduce the torque ripple and the unbalanced electromagnetic force on the rotor of the dual‐parallel rotor permanent magnet motor, a dynamic Kriging surrogate model is proposed to optimize its structural parameters. In the process of constructing the dynamic Kriging surrogate model, the concept of key sampling space is introduced, which solves the problems of low optimization efficiency and poor model accuracy of the traditional static surrogate model based on ‘one‐time’ sampling. The topological structure of the dual‐parallel rotor permanent magnet motor is introduced, and a prototype is used to verify the accuracy of the numerical model. The optimization parameters are determined, and the initial sampling space of each optimization parameter is determined according to the influence law of a single parameter on the optimization objectives. The initial sample database of the Kriging surrogate model is established, and a dynamic criterion for adding sample points is proposed. Combined with the NSGA‐II algorithm, the surrogate model is constructed and solved. The optimal solution is substituted into the numerical model, which verifies the feasibility and correctness of the proposed optimization design method. The accuracy of the dynamic Kriging surrogate model is discussed and compared with the traditional static surrogate model. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Rotor Multidisciplinary Optimization of High Speed PMSM Based on Multi-Fidelity Surrogate Model and Gradient Sequential Sampling

Cited by 4 publications

References 25 publications

Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework

Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework

A Mixed-Variable Experimental Design Method

Optimization Design of Dual‐Parallel Rotor Permanent Magnet Motor Based on Dynamic Kriging Surrogate Model

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