Control predictivo polifásico mediante dos constelaciones de vectores virtuales de tensión
DOI:
https://doi.org/10.4995/riai.2023.19205Palabras clave:
máquinas de inducción, sistemas polifásicos, mapa de rendimiento, control Predictivo, vectores virtuales de tensiónResumen
En el campo de los accionamientos eléctricos de velocidad variable ha aparecido recientemente el método predictivo basado en vectores virtuales de tensión. Este método permite reducir la contribuci´on del voltaje en el subespacio x-y, en el cual no se produce par, sino pérdidas. De este modo no sólo se limitan las pérdidas sino que se reduce la complejidad de sintonía del controlador predictivo. Los vectores virtuales de tensión se obtienen mediante combinación de vectores de tensión pertenencientes a distintas coronas pequeña, media y grande además de los vectores nulos. En una aplicación típica se elige en primer lugar la(s) corona(s) a usar y después se desarrollan los vectores virtuales. El controlador predictivo usa en cada periodo de muestreo el vector virtual más adecuado. En este trabajo se propone el uso de varios conjuntos de vectores virtuales provenientes de diferentes combinaciones de coronas. Para cada punto de operación del accionamiento eléctrico se utiliza el conjunto que proporciona mejores valores de cierto criterio de bondad. El método propuesto es validado experimentalmente usando una máquina de inducción de seis fases.
Descargas
Citas
Arahal, M. R., Barrero, F., Bermúdez, M., Satué, M. G., 2022. Predictive stator current control of a five-phase motor using a hybrid control set. IEEE Journal of Emerging and Selected Topics in Power Electronics. https://doi.org/10.1109/JESTPE.2022.3172138
Arahal, M. R., Kowal, A., Barrerro, F., Castilla, M. d. M., 2019. Optimización de funciones de coste para control predictivo de máquinas de inducci'on multifásicas. Revista Iberoamericana de Automática e Informática Industrial 16 (1), 48-55. https://doi.org/10.4995/riai.2018.9771
Arahal, M. R., Satué, M. G., Barrero, F., Ortega, M. G., 2021. Adaptive cost function FCSMPC for 6-phase IMs. Energies 14 (17), 5222. https://doi.org/10.3390/en14175222
Ben Slimene, M., Khlifi, M. A., 2022. Investigation on the effects of magnetic saturation in six-phase induction machines with and without cross saturation of the main flux path. Energies 15 (24), 9412. https://doi.org/10.3390/en15249412
Bermúdez, M., Martín, C., González-Prieto, I., Durán, M. J., Arahal, M. R., Barrero, F., 2020. Predictive current control in electrical drives: an illustrated review with case examples using a five-phase induction motor drive with distributed windings. IET Electric Power Applications 14 (8), 1291-1310. https://doi.org/10.1049/iet-epa.2019.0667
Camacho, E. F., Bordons, C., 2013. Model predictive control. Springer.
Duran, M. J., Gonzalez-Prieto, I., Gonzalez-Prieto, A., Aciego, J. J., 2022. The evolution of model predictive control in multiphase electric drives: A growing field of research. IEEE Industrial Electronics Magazine 16 (4), 29-39. https://doi.org/10.1109/MIE.2022.3169291
Elmorshedy, M. F., Xu, W., El-Sousy, F. F., Islam, M. R., Ahmed, A. A., 2021. Recent achievements in model predictive control techniques for industrial motor: A comprehensive state-of-the-art. IEEE Access 9, 58170-58191. https://doi.org/10.1109/ACCESS.2021.3073020
Entrambasaguas, P. G., Prieto, I. G., Martínez, M. J. D., Guzmán, M. B., García, F. J. B., 2018. Vectores virtuales de tensión en control directo de par para una máquina de inducción de seis fases. Revista Iberoamericana de Automática e Informática industrial 15 (3), 277-285. https://doi.org/10.4995/riai.2018.9837
Garcia-Entrambasaguas, P., Zoric, I., Gonzalez-Prieto, I., Duran, M. J., Levi, E., 2019. Direct torque and predictive control strategies in nine-phase electric drives using virtual voltage vectors. IEEE Transactions on Power Electronics 34 (12), 12106-12119. https://doi.org/10.1109/TPEL.2019.2907194
Gonçalves, P. F., Cruz, S. M., Mendes, A. M., 2019. Bi-subspace predictive current control of six-phase PMSM drives based on virtual vectors with optimal amplitude. IET Electric Power Applications 13 (11), 1672-1683. https://doi.org/10.1049/iet-epa.2019.0136
Gonzalez-Prieto, A., González-Prieto, I., Duran, M. J., Aciego, J. J., 2022. Dynamic response in multiphase electric drives: Control performance and influencing factors. Machines 10 (10), 866. https://doi.org/10.3390/machines10100866
Gonzalez-Prieto, I., Duran, M. J., Aciego, J. J., Martin, C., Barrero, F., 2017. Model predictive control of six-phase induction motor drives using virtual voltage vectors. IEEE Transactions on Industrial Electronics 65 (1), 27-37. https://doi.org/10.1109/TIE.2017.2714126
Holtz, J., Stadtfeld, S., 1983. A predictive controller for the stator current vector of AC machines fed from a switched voltage source. In: JIEE IPEC-Tokyo Conf. pp. 1665-1675.
Kali, Y., Rodas, J., Doval-Gandoy, J., Ayala, M., Gonzalez, O., 2023. Enhanced reaching-law-based discrete-time terminal sliding mode current control of a six-phase induction motor. Machines 11 (1), 107. https://doi.org/10.3390/machines11010107
Lim, C. S., Lee, S. S., Levi, E., 2022. Continuous-control-set model predictive current control of asymmetrical six-phase drives considering system nonidealities. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/TIE.2022.3206703
Lim, C.-S., Levi, E., Jones, M., Rahim, N., Hew, W.-P., Aug 2014. A comparative study of synchronous current control schemes based on FCS-MPC and PI-PWM for a two-motor three-phase drive. Industrial Electronics, IEEE Transactions on 61 (8), 3867-3878. https://doi.org/10.1109/TIE.2013.2286573
Luo, Y., Liu, C., 2018. A flux constrained predictive control for a six-phase PMSM motor with lower complexity. IEEE Transactions on Industrial Electronics 66 (7), 5081-5093. https://doi.org/10.1109/TIE.2018.2868301
Luo, Y., Liu, C., 2019. Model predictive control for a six-phase PMSM motor with a reduced-dimension cost function. IEEE Transactions on Industrial Electronics 67 (2), 969-979. https://doi.org/10.1109/TIE.2019.2901636
Mamdouh, M., Abido, M. A., 2022. Simple predictive current control of asymmetrical six-phase induction motor with improved performance. IEEE Transactions on Industrial Electronics. https://doi.org/10.1016/j.aej.2021.09.003
Martín, C., Bermúdez, M., Barrero, F., Arahal, M. R., Kestelyn, X., Durán, M. J., 2017. Sensitivity of predictive controllers to parameter variation in five-phase induction motor drives. Control Engineering Practice 68, 23-31. https://doi.org/10.1016/j.conengprac.2017.08.001
Mwasilu, F., Kim, E.-K., Rafaq, M. S., Jung, J.-W., 2017. Finite-set model predictive control scheme with an optimal switching voltage vector technique for high-performance IPMSM drive applications. IEEE Transactions on Industrial Informatics 14 (9), 3840-3848. https://doi.org/10.1109/TII.2017.2787639
Preindl, M., Bolognani, S., 2013. Model predictive direct speed control with finite control set of PMSM drive systems. IEEE Transactions on Power Electronics 28 (2), 1007-1015. https://doi.org/10.1109/TPEL.2012.2204277
Riveros, J. A., Yepes, A. G., Barrero, F., Doval-Gandoy, J., Bogado, B., Lopez, O., Jones, M., Levi, E., 2012. Parameter identification of multiphase induction machines with distributed windings-part 2: Time-domain techniques. IEEE Transactions on Energy Conversion 27 (4), 1067-1077. https://doi.org/10.1109/TEC.2012.2219862
Satué, M. G., Arahal, M. R., Ramírez, D. R., 2023. Estimación de intensidades rotóricas en máquinas polifásicas para control predictivo. Revista Iberoamericana de Automática e Informática industrial 20 (1), 25-31. https://doi.org/10.4995/riai.2022.17153
Serra, J., Cardoso, A. J. M., 2022. A simplified model predictive control for asymmetrical six-phase induction motors that eliminates the weighting factor. Machines 10 (12), 1189. https://doi.org/10.3390/machines10121189
Shawier, A., Habib, A., Mamdouh, M., Abdel-Khalik, A. S., Ahmed, K. H., 2021. Assessment of predictive current control of six-phase induction motor with different winding configurations. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3085083
Tawfiq, K. B., Ibrahim, M. N., Sergeant, P., 2022. Power loss analysis of a fivephase drive system using a synchronous reluctance motor and an indirect matrix converter with reduced switching losses. Machines 10 (9), 738. https://doi.org/10.3390/machines10090738
Wang, H.,Wu, X., Zheng, X., Yuan, X., 2022. Model predictive current control of nine-phase open-end winding pmsms with an online virtual vector synthesis strategy. IEEE Transactions on Industrial Electronics 70 (3), 2199-2208. https://doi.org/10.1109/TIE.2022.3174241
Wei, J., Kong, X., Tao, W., Zhang, Z., Zhou, B., 2022. The torque ripple optimization of open-winding permanent magnet synchronous motor with direct torque control strategy over a wide bus voltage ratio range. IEEE Transactions on Power Electronics 37 (6), 7156-7168. https://doi.org/10.1109/TPEL.2022.3146155
Xue, C., Song, W., Feng, X., 2017. Finite control-set model predictive current control of five-phase permanent-magnet synchronous machine based on virtual voltage vectors. IET Electric Power Applications 11 (5), 836-846. https://doi.org/10.1049/iet-epa.2016.0529
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2023 Manuel Garrido Satué, Manuel Ruiz Arahal, Daniel Rodríguez Ramírez, Federico Barrero García
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Esta revista se publica bajo una Licencia Creative Commons Attribution-NonCommercial-CompartirIgual 4.0 International (CC BY-NC-SA 4.0)
Datos de los fondos
-
Ministerio de Ciencia, Tecnología e Innovación Productiva
Números de la subvención TED2021-129558B- C22 -
Ministerio de Ciencia, Tecnología e Innovación Productiva
Números de la subvención PID2021-125189OB-I00