Metamodeling of Rotating Electric Machinery

Sudhoff, Scott D.; Sahu, Raj

doi:10.1109/tec.2018.2793160

Cited by 16 publications

(16 citation statements)

References 14 publications

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“…A separate model has to be defined for any objective and any constraint considered for the optimization problem. In the past, surrogate modeling was already successfully applied in the field of electric machine design [7], [36], [37], but very seldom for modeling the impact of tolerances.…”

Section: Surrogate Model Assisted Design Evaluationmentioning

confidence: 99%

Multiobjective electric machine optimization for highest reliability demands

Bramerdorfer

2020

Trans. Electr. Mach. Syst.

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This article is about illustrating a workflow for incorporating reliability measures to typical electric machine design optimization scenarios. Such measures facilitate comparing designs not only for rated conditions, but also allow to analyze their performance in the presence of unevitable tolerances. Consequently, by additionally considering reliability or robustness as objectives compared to conventional optimization scenarios, designs featuring low parameter sensitiveness can be obtained. The analysis of the design's reliability as part of solving optimization problems involves a significant increase in required numerical evaluations. To minimize the associated prolongation of the runtime, an approach featuring a design of experiments based reduction of required computations and a consequent surrogate modeling technique is presented here. After successful training, the metamodel can be applied for fast evaluating lots of different parameter combinations. A test problem is defined and analyzed. Based on the observed findings, the necessity of incorporating robustness evaluations to machine design optimization becomes evident. In addition, the derived models allow for studying the impact of any toleranceaffected parameter on the machine performance in detail. This facilitates further beneficial studies, as for instance the analysis of selected changes of tolerance levels rather than a general minimization of the respective ranges which usually is associated with high production cost.

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Section: Surrogate Model Assisted Design Evaluationmentioning

confidence: 99%

Multiobjective electric machine optimization for highest reliability demands

Bramerdorfer

2020

Trans. Electr. Mach. Syst.

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“…Unfortunately, this model is computationally expensive for the overall generator-rectifier system optimization problem. To reduce the computational burden of electric machine design but still retain the details of its design, the authors in [15] present a metamodeling procedure for electric machines. The PMAC metamodel is advantageous relative to traditional machine scaling equations as it does detailed analysis of the PMAC generator, and captures its core and resistive losses.…”

Section: A Metamodeling Of Permanent Magnet Ac Generatormentioning

confidence: 99%

“…The PMAC metamodel is advantageous relative to traditional machine scaling equations as it does detailed analysis of the PMAC generator, and captures its core and resistive losses. The metamodel in [15] quickly estimates the trade-off between the machine mass and loss, and poses a reduced computational burden to the overall system optimization.…”

Section: A Metamodeling Of Permanent Magnet Ac Generatormentioning

confidence: 99%

Design Paradigm for Modular Multilevel Converter-Based Generator Rectifier Systems

Sahu

Sudhoff

2020

IEEE Open J. Power Energy

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Modular Multilevel Converters (MMC) are being widely considered for medium to high voltage DC applications. Designing such converters through multi-objective optimization is of interest because such an approach allows the trade-off between competing objectives (for example mass and loss) to be explicitly and quantitatively identified. In this work, an optimization based design paradigm for MMC based generator rectifier systems is proposed. Such development typically requires detailed component design and simulation models for the electric machine and converter which are computationally expensive. As an alternative, the proposed work utilizes an electric machine metamodel, inductor metamodel, and high-speed steady-state simulation model for the MMC to facilitate multi-objective optimization minimizing system metrics of interest while satisfying system constraints. A case study is undertaken to demonstrate the functionality of the proposed design paradigm.

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“…Some S3D components are automatically scalable, based on a small number of inputs. One example is a scalable motor developed by Sudhoff et al [8] in which the user specifies rated torque, speed, and voltage and a ratio value for length, diameter and mass. Then, for a selected electro-magnetic torque density and aspect ratio type, the component calculates its own dimensions, weight, efficiency, power and losses.…”

Section: Equipment Property Variationmentioning

confidence: 99%

Expanding the Design Space Explored by S3D

Chalfant

Wang

Triantafyllou

2019

2019 IEEE Electric Ship Technologies Symposium (ESTS)

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Modern design processes such as set-based design and TIES (Technology Identification, Evaluation and Selection) depend on the ability to explore a large design space rather than attempting to optimize a single design. In this paper, we investigate methods for expanding the design space that can be explored using the S3D (Smart Ship System Design) software environment. We then detail the most recent advancements in the templating process, with the goal of automated system assembly and evaluation using pre-designed system segments called templates.

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Metamodeling of Rotating Electric Machinery

Cited by 16 publications

References 14 publications

Multiobjective electric machine optimization for highest reliability demands

Multiobjective electric machine optimization for highest reliability demands

Design Paradigm for Modular Multilevel Converter-Based Generator Rectifier Systems

Expanding the Design Space Explored by S3D

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