Abstract
To optimize the performance of permanent magnet synchronous motor (PMSM), a multidisciplinary design optimization (MDO) method is proposed which considers both motor structure and controller design. Surrogate models are constructs to save computing resources and accelerate the optimization process. In order to solve the problem that the selection of surrogate model depends heavily on the experience of engineers, an intelligent surrogate model selection method (ISMSM) is proposed to obtain a proper surrogate model. Based on ISMSM and the MDO method, the PMSM design parameters are optimized, and the results show a significant improvement in overall performance.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2024 IEEE 7th International Electrical and Energy Conference, CIEEC 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2133-2137 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350359558 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 7th IEEE International Electrical and Energy Conference, CIEEC 2024 - Harbin, China Duration: 10 May 2024 → 12 May 2024 |
Publication series
| Name | Proceedings of 2024 IEEE 7th International Electrical and Energy Conference, CIEEC 2024 |
|---|
Conference
| Conference | 7th IEEE International Electrical and Energy Conference, CIEEC 2024 |
|---|---|
| Country/Territory | China |
| City | Harbin |
| Period | 10/05/24 → 12/05/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- PMSM
- electric vehicles
- intelligent surrogate model selection method
- multidisciplinary design optimization
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