Research on parameter optimization design of coreless transformer based on genetic algorithm
Wenshuang Qin, Yi Zhang, Yufang Lu · 2025
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Description
Wenshuang Qin and co-authors tuned a wireless power device with an evolution-inspired search in this 2025 paper. The device is a coreless transformer: two flat coils that pass energy across a gap with no iron core. Its efficiency swings with coil spacing, working frequency, and the load it feeds.
A random forest model first learned to predict efficiency from those settings. A genetic algorithm then bred setting combinations, keeping the best, until efficiency peaked. The team built the winning design and tested the real circuit. Efficiency reached about seventy-two percent, a large jump over the untuned design. The result shows data-driven tuning can lift simple power hardware a long way.
Catalog record
| CREATOR | Wenshuang Qin, Yi Zhang, Yufang Lu |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 40 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |