Research on parameter optimization design of coreless transformer based on genetic algorithm Article Swipe

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YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1038/s41598-025-27671-w

This study found that the inter-coil spacing (H) of a coreless transformer, the operating frequency (f₀), the load (R_L) on the transformer's secondary circuit, and the actual operating frequency (f) all affect the transmission efficiency (η) of the transformer. To address this, a random forest regression model was used to predict the transmission efficiency (η) as a function of the parameters (f₀, H, R_L, f). A genetic algorithm was employed to optimize the parameters (f₀, H, R_L, f) in order to maximize η. Based on the optimization results, efficient transformer and circuit designs were developed. After simulation verification, a prototype circuit was fabricated and tested. The results showed that the transmission efficiency of the planar coreless transformer, optimized using the genetic algorithm, reached 71.7%, a 54.8% improvement over the unoptimized circuit and a 17.7% increase compared to the directly designed transformer circuit without optimization. This demonstrates the effectiveness of the proposed optimization approach.

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Type: article
Language: en
Landing Page: https://doi.org/10.1038/s41598-025-27671-w
PDF: https://www.nature.com/articles/s41598-025-27671-w.pdf
OA Status: gold
References: 6
OpenAlex ID: https://openalex.org/W4417321893

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OpenAlex ID: https://openalex.org/W4417321893

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DOI: https://doi.org/10.1038/s41598-025-27671-w

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Title: Research on parameter optimization design of coreless transformer based on genetic algorithm

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-12-15

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Authors: Wen Qin, Yi Zhang, Yufang Lü

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Landing page: https://doi.org/10.1038/s41598-025-27671-w

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PDF URL: https://www.nature.com/articles/s41598-025-27671-w.pdf

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OA URL: https://www.nature.com/articles/s41598-025-27671-w.pdf

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Cited by: 0

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References (count): 6

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