Optimization Design of High-Power High-Frequency Transformer Based on Multi-Objective Genetic Algorithm

Zhang, Ke; Chen, Wu; Cao, Xiaopeng; Song, Zhanfei; Qiao, Guifang; Sun, Li

doi:10.1109/peac.2018.8590371

Cited by 17 publications

(7 citation statements)

References 7 publications

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“…The turbulence model adopts RNG model. The RNG model is a Renormalization Group Based on the theory proposed, as the standard model correction equation, it can better simulate boundary layer flow, strong adverse pressure gradient flow, separation flow, rotating flow, etc [2] .…”

Section: Mathematical Modelmentioning

confidence: 99%

Unmanned aerial vehicle fuel tank structure design optimization based on Flow-EFD fluid simulation

Deng

Jiang²,

Wang³

et al. 2023

J. Phys.: Conf. Ser.

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Fuel quantity indication and fuel low level warning design is an important technology for unmanned aerial vehicle design with long distance flight capability. Since the size and shape of overflow holes opened on fuel tank rib structure impact the fuel leakage rate and in turn impact whether fuel low level warning will be triggered at expected time, this article use RNG-turbulence model based on Flow-EFD fluid simulation to compare three different overflow hole design schemes and get the conclusion that several rectangular holes design has negative impact on fuel level descending and will not cause nuisance fuel low level alert under large pitch angle.

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Section: Mathematical Modelmentioning

confidence: 99%

Unmanned aerial vehicle fuel tank structure design optimization based on Flow-EFD fluid simulation

Deng

Jiang²,

Wang³

et al. 2023

J. Phys.: Conf. Ser.

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“…According to the heat transfer principle and relative aging calculation, the difference equation model of temperature rise and life loss of traction transformer in traction substation is established to optimize the capacity of traction transformer in new traction substation. In [13], the efficiency, insulation, heat dissipation, and stray parameters of transformers are taken into account. The transformer loss and leakage inductance are taken as optimization objectives.…”

Section: Capacity Optimization Of Traction Transformer Based On Algor...mentioning

confidence: 99%

Review on Capacity Optimization of Traction Transformer for High-Speed Railway

Li¹,

Xiao²,

Lü³

et al. 2022

Energy Engineering

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In electrified railways, traction load not only fluctuates between peaks and valleys, but also has a situation of low utilization rate of average load throughout the day and short overload. The traction transformer selects the capacity with the peak load as the demand boundary, which will cause the capacity utilization rate to be low and even lead to the economic decline of the traction power supply system. This article summarizes the existing configuration methods for capacity optimization of traction transformer. Then under the conditions of energy storage and new energy access to traction power supply system, the three aspects are described as follows. Firstly, the energy storage device is connected to the system, which can pull the capacity of traction transformer to achieve peak shifting and valley filling. Then, the possibility of integrated configuration of new energy and traction power supply system to optimize the capacity of traction transformer and the methods of optimal configuration of traction transformer capacity by using new energy such as wind and light are summarized. Finally, this paper discusses the current structure of new energy access to traction power supply system, and it looks forward to the feasibility of new energy access to traction power supply system cooperating with energy storage devices to optimize the capacity of traction transformer.

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“…For the design optimization of a high-frequency transformer, there are many objectives, such as minimizing the loss and volume. Regarding the design optimization parameters, dimensions (as shown in Figure 1d) and core materials (like nanocrystalline or amorphous) can be considered [29][30][31][32]. Detailed optimization models can be referred to these works as well.…”

Section: Deterministic Design Optimizationmentioning

confidence: 99%

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

Lei

Bramerdorfer

et al. 2021

Applied Sciences

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This paper reviews the recent developments of design optimization methods for electromagnetic devices, with a focus on machine learning methods. First, the recent advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust design optimization of electromagnetic devices are overviewed. Second, a review is presented to the performance prediction and design optimization of electromagnetic devices based on the machine learning algorithms, including artificial neural network, support vector machine, extreme learning machine, random forest, and deep learning. Last, to meet modern requirements of high manufacturing/production quality and lifetime reliability, several promising topics, including the application of cloud services and digital twin, are discussed as future directions for design optimization of electromagnetic devices.

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Optimization Design of High-Power High-Frequency Transformer Based on Multi-Objective Genetic Algorithm

Cited by 17 publications

References 7 publications

Unmanned aerial vehicle fuel tank structure design optimization based on Flow-EFD fluid simulation

Unmanned aerial vehicle fuel tank structure design optimization based on Flow-EFD fluid simulation

Review on Capacity Optimization of Traction Transformer for High-Speed Railway

Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions

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