Abstract
This paper explores the electromagnetic design of Rim-Driven Propulsors (RDP), focusing on the rotor-stator configuration, material optimization, and multi-objective design parameters. The study employs surrogate modeling techniques, particularly Support Vector Regression (SVR), to optimize critical design aspects, including torque, efficiency, and thermal performance. Finite Element (FE) simulations are used to generate data for the surrogate models, while Genetic Algorithms (GA) explore the trade-offs among competing objectives. The results demonstrate a significant improvement in system performance, offering a highly efficient and robust solution for modern electric propulsion systems in aerospace applications.
| Original language | English |
|---|---|
| Title of host publication | 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3546-3553 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798331542979 |
| DOIs | |
| State | Published - 2025 |
| Event | 8th IEEE International Electrical and Energy Conference, CIEEC 2025 - Changsha, China Duration: 16 May 2025 → 18 May 2025 |
Publication series
| Name | 2025 IEEE 8th International Electrical and Energy Conference, CIEEC 2025 |
|---|
Conference
| Conference | 8th IEEE International Electrical and Energy Conference, CIEEC 2025 |
|---|---|
| Country/Territory | China |
| City | Changsha |
| Period | 16/05/25 → 18/05/25 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Electric Propulsion
- Electromagnetic Design
- Magnets
- Optimization
- Rim Driven Fan
- Rim Driven Propulsor
- Surrogate Modeling
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