Self-learning MTPA control of interior permanent magnet synchronous machine drives based on virtual signal injection
Yazarlar (4)
Tianfu Sun
The University Of Sheffield, İngiltere
The University Of Sheffield, İngiltere
Jiabin Wang
The University Of Sheffield, İngiltere
The University Of Sheffield, İngiltere
Doç. Dr. Mikail KOÇ The University Of Sheffield, Türkiye
Xiao Chen
The University Of Sheffield, İngiltere
The University Of Sheffield, İngiltere
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/IEMDC.2015.7409192 | ||
| Kongre Adı | 2015 IEEE International Electric Machines Drives Conference (IEMDC) | ||
| Kongre Tarihi | 10-05-2015 / 13-05-2015 | ||
| Basıldığı Ülke | Amerika Birleşik Devletleri | Basıldığı Şehir | Coeur D’Xxalene, Id, Usa |
| Bildiri Linki | https://ieeexplore.ieee.org/document/7409192 | ||
| Özet |
| This paper describes a novel self-learning maximum torque per ampere (MTPA) control scheme for interior permanent magnet synchronous machine (IPMSM) drives to achieve fast dynamic response in tracking the MTPA points without accurate prior knowledge of machine parameters. The proposed self-learning control scheme (SLC) generates the optimal d-axis current command for MTPA operation after training. Virtual signal injection control (VSIC), which has been recently developed as a novel parameter-independent MTPA points tracking scheme, is utilized to train the SLC and compensate the error of the SLC during its operation. In this way, the proposed SLC can achieve the MTPA operation accurately with fast response and the online training of the SLC will not affect MTPA operation of IPMSM drives. The proposed control scheme is verified by simulations under various operation conditions on a prototype IPMSM drive system. |
| Anahtar Kelimeler |
| Curve fitting | Maximum torque per ampere control (MTPA) | Permanent magnet synchronous machine (IPMSM) | Recursive least square (RLS) | Self-learning control (SLC) | Signal injection | Signal processing | Torque control | Virtual signal injection (VSIC) |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 9 |
| Web of Science | 48 |