Multi-objective optimization of a flux switching wound field machine using a response surface-based multi-level design approach
This study introduces a novel multilevel design optimization approach for enhancing the performance of brushless flux-switching wound-field machines (FSWFMs) in electric vehicles (EVs) and industrial drives. The proposed methodology targets key performance metrics namely, high torque, efficiency, po...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025000763 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This study introduces a novel multilevel design optimization approach for enhancing the performance of brushless flux-switching wound-field machines (FSWFMs) in electric vehicles (EVs) and industrial drives. The proposed methodology targets key performance metrics namely, high torque, efficiency, power factor, and low torque ripple through a structured sensitivity analysis categorized into non-sensitive, mild-sensitive, and strong-sensitive levels. Using the Response Surface Method (RSM), Min-Max Search, and Multi-Objective Genetic Algorithms (MOGA), the Response Surface Multi-Level Optimization (RSMLO) method effectively harmonizes these competing objectives. The optimization process resulted in an 11% increase in average torque and a 69.06% reduction in torque ripple, demonstrating significant performance gains. These results underscore the potential of the RSMLO method as a robust tool for the advanced design of electric machines, offering substantial improvements in both performance and efficiency, and positioning it as a critical framework for future EV and industrial drive applications. |
|---|---|
| ISSN: | 2590-1230 |