| Proj No. | A1120-251 |
| Title | AI-Driven Optimization of PCB-Based Wireless Power Transfer Resonators |
| Summary | Printed-circuit-board (PCB)-based wireless power transfer (WPT) resonators are increasingly popular as emerging applications push operating frequencies into the tens of megahertz (MHz) and industrial requirements demand disc-shaped, lightweight designs. While the finite element method (FEM) is a fundamental tool for designing these resonators, its computational intensity and time requirements pose significant challenges. Leveraging rapid advancements in artificial intelligence (AI), this project proposes an AI-based optimization scheme to determine the optimal geometric configuration of PCB coils, bypassing the need for FEM simulations and significantly enhancing design efficiency. The selected student will work collaboratively with a postgraduate student to optimize coil geometry for improved WPT system performance. AI technologies will be applied to systematically explore a range of geometric parameter combinations, ultimately identifying the optimal design. The final outcomes will be validated using a MHz-band WPT system, demonstrating the practical benefits of the AI-driven approach. |
| Supervisor | Ast/P Yang Yun (Loc:S2 > S2 B2C > S2 B2C 105, Ext: +65 67905406) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Water & Energy Research Laboratory (Loc: S2.1-B3-03) |
| Single/Group: | Single |
| Area: | Electrical Power and Energy |
| ISP/RI/SMP/SCP?: |