Screening and response surface method applied to the numerical optimization of electromagnetic devices

Gillon, F.; Brochet, P.

doi:10.1109/20.877647

Cited by 39 publications

(3 citation statements)

References 3 publications

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“…-Especially when the evaluation of the objective function is computationally expensive, it is recommended to carry out the optimization method on the basis of a surrogate model (indirect optimization methods). Such a simplified model can be obtained by expert knowledge on the application [58], by design space reduction [17], by a response surface methodology [17] or by space mapping [28] or manifold mapping [15]. Here, a direct optimization procedure is used.…”

Section: Optimization Methodsmentioning

confidence: 99%

Robust shape optimization of electric devices based on deterministic optimization methods and finite-element analysis with affine parametrization and design elements

et al. 2018

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In this paper, gradient-based optimization methods are combined with finite-element modeling for improving electric devices. Geometric design parameters are considered by piecewise affine parametrizations of the geometry or by the design element approach, both of which avoid remeshing. Furthermore, it is shown how to robustify the optimization procedure, that is, how to deal with uncertainties on the design parameters. The overall procedure is illustrated by an academic example and by the example of a permanent-magnet synchronous machine. The examples show the advantages of deterministic optimization compared to standard and popular stochastic optimization procedures such as particle swarm optimization.

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Section: Optimization Methodsmentioning

confidence: 99%

Robust shape optimization of electric devices based on deterministic optimization methods and finite-element analysis with affine parametrization and design elements

et al. 2018

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“…A literature review considering optimization problems with surrogate models yield some general information [8][9][10]. The workflow of determining the solution can be illustrated as in Figure 2.…”

Section: Deterministic Methods With Surrogate Modelsmentioning

confidence: 99%

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 2

Schmelcher

Büning

Kreisköther

et al. 2018

The Economy, Sustainable Development, and Energy International Conference

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Designing energy-efficient electric motor is a task where multiple goals have to be achieved at once. To find the best design possible, different approaches have been developed. In part one of this multipart paper, the characteristics of the design optimization problem and methods to solve them have been presented. Part two will deal with the different types of model descriptions and how the fundamental workflows look like. The third and last paper will evaluate the findings concerning the solution methods of the design optimization problem of electric motors. As a consequence, requirements for a new improved optimization method are deduced and presented.

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“…The permanent-magnet synchronous motor design process involves several parameters, each having a different degree of influence on the optimization objective. Furthermore, the DOE can quantify the degree of influence of each parameter on the objective function and screen out the significant factors [7][8][9]. Response surface methodology is often used in the optimal design of electromagnetic devices to fit a more accurate model [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Design Optimization of an Automotive Permanent-Magnet Synchronous Motor by Combining DOE and NMGWO

Cui,

Zhang

et al. 2023

Electronics

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This study proposes an optimization methodology for automotive permanent-magnet synchronous motors (PMSMs) to achieve maximum efficiency, maximum average torque, and minimum torque ripple. Many geometrical parameters can be used to define the PMSM of an automobile. To identify the most significant parameters for optimization, the fractional factorial design of the design of experiment (DOE) was employed for screening, considering the interaction effects. The central composite design was used to construct the proxy model between the optimization target and optimization variable, and the effectiveness of the model was judged. Aiming at the multi-objective optimization problem of a motor, a new mechanism for grey wolf optimizer (NMGWO) algorithm combining an elite reverse learning strategy, a local search strategy, and a nonlinear control parameter strategy is innovatively proposed. This algorithm was applied to solve the multi-objective optimization model. The numerical calculation results show that this is an effective optimization design method that can improve the performance of automotive PMSMs. The effectiveness of the NMGWO algorithm on the optimization results of permanent-magnet synchronous motors is verified by the experimental results.

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Screening and response surface method applied to the numerical optimization of electromagnetic devices

Cited by 39 publications

References 3 publications

Robust shape optimization of electric devices based on deterministic optimization methods and finite-element analysis with affine parametrization and design elements

Robust shape optimization of electric devices based on deterministic optimization methods and finite-element analysis with affine parametrization and design elements

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 2

Design Optimization of an Automotive Permanent-Magnet Synchronous Motor by Combining DOE and NMGWO

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