Muestra métricas de impacto externas asociadas a la publicación. Para mayor detalle:
| Indexado |
|
||
| DOI | 10.30941/CESTEMS.2021.00012 | ||
| Año | 2021 | ||
| Tipo |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
To reduce the torque ripple in motors resulting from the use of conventional direct torque control (DTC), a model predictive control (MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper. Two new look-up tables are proposed, these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states. Finite control set model predictive control (FCS-MPC) has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque. Finally, the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Dan, Hanbing | - |
Central South University - China
|
| 2 | Zeng, Peng | - |
Central South University - China
|
| 3 | Xiong, Wenjing | - |
Central South University - China
|
| 4 | Wen, Meng | - |
Yunnan Mobile Communication Company Limited - China
|
| 5 | Su, Mei | - |
Central South University - China
|
| 6 | Rivera, Marco | - |
Universidad de Talca - Chile
|
| Fuente |
|---|
| National Natural Science Foundation of China |
| Natural Science Foundation of Hunan Province |
| Hunan Provincial Key Laboratory of Power Electronics Equipment and Grid |
| Agradecimiento |
|---|
| This work was supported in part by the Hunan Provincial Key Laboratory of Power Electronics Equipment and Grid under Grant 2018TP1001, in part by the National Natural Science Foundation of China under Grant 61903382, 51807206, 61933011, in part by the Major Project of Changzhutan Self-Dependent Innovation Demonstration Area under Grant 2018XK2002, in part by the Natural Science Foundation of Hunan Province, China under Grant 2020JJ5722 and 2020JJ5753. (Corresponding author: Wenjing Xiong). |