Fault-Tolerant Control for Non-sinusoidal Seven-phase PMSMs with Similar Copper Losses

Autor: Duc Tan Vu, Ngac Ky Nguyen, Eric Semail, Trung Hai Do
Přispěvatelé: Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 (L2EP), Centrale Lille-Université de Lille-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Thai Nguyen University, We would like to thank the CE2I project sponsored byEuropean Regional Development Fund, French State, andFrench Region of Hauts-de-France for the financial support.
Rok vydání: 2022
Předmět:
Zdroj: 2022 IEEE 9TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE 2022)
2022 IEEE 9TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE 2022), Jul 2022, Nha Trang, Vietnam. ⟨10.1109/ICCE55644.2022.9852050⟩
DOI: 10.1109/icce55644.2022.9852050
Popis: This paper proposes a strategy using new transformation matrices to calculate new current references when a non-sinusoidal seven-phase permanent magnet synchronous machine (PMSM) has an open-circuited phase. The new current references allow to obtain a smooth torque with similar copper losses in the remaining healthy phases even when the back electromotive force (back-EMF) is non-sinusoidal. A real-time current learning process using an adaptive linear neural network (Adaline) is applied to extract from measured currents useful harmonic components in torque generation. It improves torque quality, especially at high speed, even when standard proportional-integral (PI) controllers are applied. In addition, similar copper losses in the remaining phases with the new current references can avoid overheating of windings. The effectiveness of the proposed control strategy is validated by numerical results. We would like to thank the CE2I project sponsored by European Regional Development Fund, French State, and French Region of Hauts-de-France for the financial support.
Databáze: OpenAIRE