| Proj No. | A1128-251 |
| Title | AI-Driven Receiver Coil Optimization for Enhanced Dynamic Wireless Power Transfer in In-Motion EV Charging |
| Summary | Dynamic Wireless Power Transfer (DWPT) has emerged as a promising technology for in-motion electric vehicle (EV) charging, offering significant advantages over stationary methods by enabling vehicles to charge while in motion. This approach reduces the reliance on large battery capacities and minimizes charging downtime. The performance of DWPT systems hinges on the design of the receiver coil, which directly influences power transfer capability, misalignment tolerance, and overall system efficiency. This project focuses on optimizing the receiver coil design by exploring critical factors such as coil geometry, shielding materials, and compensation topologies. The primary goal is to enhance power transfer efficiency, reduce energy losses, and improve misalignment tolerance through an advanced optimization framework. This framework will integrate electromagnetic modeling, simulation techniques, and AI-based algorithms to identify the optimal design parameters. The selected student will collaborate with research staff and a postgraduate researcher to refine system models, develop optimization algorithms, and validate the proposed designs using an industrial-scale dynamic IPT system. The insights gained from this project will contribute to the advancement of high-efficiency DWPT systems, supporting the broader adoption of in-motion EV charging in real-world applications. |
| Supervisor | Ast/P Yang Yun (Loc:S2 > S2 B2C > S2 B2C 105, Ext: +65 67905406) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Clean Energy Research (Loc: S2-B7c-05) |
| Single/Group: | Single |
| Area: | Electrical Power and Energy |
| ISP/RI/SMP/SCP?: |