Artificial Intelligence Applications in High-Frequency Magnetic Components Design for Power Electronics Systems: An Overview

Shen, Xiaobing; Zuo, Yu; Kong, Jiaze; Martinez, Wilmar

doi:10.1109/tpel.2024.3381431

Cited by 1 publication

(2 citation statements)

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Section: Discussionmentioning

confidence: 99%

“…Other models based on artificial intelligence (AI) [42][43][44] can also be used to accurately estimate temperature distribution. Indeed, AI is a promising tool, especially suitable for the design of HF magnetic components and their thermal management [44]. For example, AI models can lead to more efficient thermal management and automatic heatsink design, as it was developed, in [45], for the heatsink optimization of air-cooled power modules.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Thermal Resistance Modeling for the Optimal Design of EE and E/PLT Core-Based Planar Magnetics

Bakri,

Margueron,

Le Moigne

et al. 2024

Energies

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With the integration of power electronic converters and components, an accurate thermal design becomes essential. Hence, precise thermal models for components are needed for their optimal design. This paper focuses on the development of an analytical model for the design of thermal resistance of planar magnetic cores (PMC). Based on computational fluid dynamic (CFD) simulations, the PMC design thermal resistance variation is studied, according to ambient temperature and level of losses. Then, a polynomial equation is developed to model those variations, and coefficients are deduced for all the sizes of PMC. This analytical model, useful for designers, is finally validated with thermal measurements on a planar transformer prototype.

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