| Autor: |
Cong Li, Qi Zhang, Rongwu Zhu, Jiahao Zhang, Hui Yang, Fujin Deng, Xiangdong Sun |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 162347-162358 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3444056 |
| Popis: |
Nonlinearities of inductor’s soft magnet, converter’s time-varying mode and control delays limit the grid-side power quality improvement capability of interleaved boost Power Factor Correction (PFC) circuit. The traditional internal model principle-based approaches are widely used to improve the power quality, but the expense is the reduce of certain stability. Hence, this paper proposes a data-driven online compensation method to address this trade-off between control accuracy, power quality and stable margin. This method involves recording control data of a multi-frequency proportional resonant (PR) controller under various input conditions. The collected data is preprocessed and used to establish a regression compensation model through multivariate nonlinear regression. Finally, this regression model is applied to the compensation loop of a lower-order controller to improve power quality of the PFC while ensuring sufficient stable margin. Experiments verify the practical feasibility and the effectiveness of the proposed data-driven control method. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
