Predictive torque control of induction motor drive with reduction of torque and flux ripple

• Autorzy: Kiani Babak , Mozafari Babak , Soleymani Soodabeh , Mohammadnezhad Shourkaei Hosein

Identyfikatory

DOI

10.24425/bpasts.2021.137727

• Języki publikacji: EN

Abstrakty

EN

The continuing efforts for reduction of the torque and flux ripples using Finite Set Model Predictive Direct Torque Control methods (FS-MPDTC) have been currently drowning a great attention from the academic communities and industrial applications in the field of electrical drives. The major problem of high torque and flux ripples refers to the consideration of just one active voltage vector at the whole control period. Implementation of two or more voltage vectors at each sampling time has recently been adopted as one of the practical techniques to reduce both the torque and flux ripples. Apart from the calculating challenge of the effort control, the parameter dependency and complexity of the duty ratio relationships lead to reduction of the system robustness. those are two outstanding drawbacks of these methods. In this paper, a finite set of the voltage vectors with a finite set of duty cycles are employed to implement the FS-MPDTC of induction motor. Based on so-called Discrete Duty Cycle- based FS-MPDTC (DDC-FS-MPDTC), a base duty ratio is firstly determined based on the equivalent reference voltage. This duty ratio is certainly calculated using the command values of the control system, while the motor parameters are not used in this algorithm. Then, two sets of duty ratios with limit members are constructed for two adjacent active voltage vectors supposed to apply at each control period. Finally, the prediction and the cost function evaluation are performed for all of the preselected voltage vectors and duty ratios. However, the prediction and the optimization operations are performed for only 12 states of inverter. Meanwhile, time consuming calculations related to SVM has been eliminated. So, the robustness and complexity of the control system have been respectively decreased and increased, and both the flux and torque ripples are reduced in all speed ranges. The simulation results have verified the damping performance of the proposed method to reduce the ripples of both the torque and flux, and accordingly the experimental results have strongly validated the aforementioned statement.

Słowa kluczowe

EN

FS-MPTC; induction motor; duty ratio; voltage vector; torque; flux ripples

PL

FS-MPTC; silnik indukcyjny; cło; wektor napięcia; moment obrotowy; fala strumienia; tętnienie momentu obrotowego

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2021
• Tom: Vol. 69, nr 4
• Strony: art. no. e137727
• Opis fizyczny: Bibliogr. 37 poz., rys., tab.

Twórcy

autor

Kiani Babak

• Department of Electrical Engineering, Science and research Branch, Islamic Azad University, Tehran, IRAN

autor

Mozafari Babak

• Department of Electrical Engineering, Science and research Branch, Islamic Azad University, Tehran, IRAN

autor

Soleymani Soodabeh

• Department of Electrical Engineering, Science and research Branch, Islamic Azad University, Tehran, IRAN

autor

Mohammadnezhad Shourkaei Hosein

• Department of Electrical Engineering, Science and research Branch, Islamic Azad University, Tehran, IRAN

Bibliografia

• [1] J.P. Wach, “Maximum Torque Control of 3-phase induction motor drives,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 2, pp. 433–445, 2018.
• [2] A. Sikorski, K. Kulikowski, and M. Korzeniewski, “Modern Direct Torque and Flux Control methods of an induction machine supplied by three-level inverter,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 61, no. 4, pp. 771–778, 2013.
• [3] D. Stando and M.P. Kazmierkowski, “Constant switching frequency predictive control scheme for three-level inverter-fed sensorless induction motor drive,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 68, no. 5, pp. 1057–1068, 2020.
• [4] V. Talavat, S. Galvani, and M. Hajibeigy, “Direct predictive control of asynchronous machine torque using matrix converter,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 4, pp. 773–788, 2018.
• [5] I. Takahashi and T. Noguchi, “A new quick response and high efficiency control strategy of an induction motor,” IEEE Trans. Power App., vol. IA-22, no. 5, pp. 820–827, Sept. 1986, doi: 10.1109/TIA.1986.4504799.
• [6] M. Depenbrock, “Direct self-control (DSC) of a inverter fed induction machine,” IEEE Trans. Power Electron., vol. 3, no. 4, pp. 420–429, Oct. 1988.
• [7] Y.-S. Lai and J.-H. Chen, “A new approach to direct torque control of induction motor drives for constant inverter switching frequency and torque ripple reduction,” IEEE Trans. Energy. Convers., vol., 16, no. 3, pp. 220–227, Sep. 2001.
• [8] C. Lascu, I. Boldea, and F. Blaabjerb, “A modified direct torque control for induction motor sensorless drive,” IEEE Trans. Ind. Appl., vol. 36, no. 1, pp. 122–130, Jan/Feb. 2000.
• [9] L. Tang, L. Zhong, M. Rahman, and Y. Hu, “A novel direct torque controlled interior permanent magnet synchronous machine drive with low ripple in flux and torque and fixed switching frequency,” IEEE Trans. Ind. Appl., vol. 19, no. 2, pp. 346–354, Mar. 2004.
• [10] R. Narayan and D.B. Subudhi, “Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 20, no.3, pp. 363–376, 2010.
• [11] I. Bakhti, S. Chaouch, and A. Maakouf, “High performance backstepping control of induction motor with adaptive sliding mode observer,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 21, no.3, pp. 331–344, 2011.
• [12] B. Kenny and R. Lorenz, “Stator- and rotor-flux-based deadbeat direct torque control of induction machines,” IEEE Trans. Ind. Appl., vol. 39, no. 4, pp. 1093–1101, Jul/Aug. 2003.
• [13] J. Rodriguez, M.P. Kazmierkowski, J. Espinoza, P. Zanchetta, H. Abu-Rub, H. Young, and C.A. Rojas, “State of the art of finite control set model predictive control in power electronics,” IEEE Trans. Ind. Inform., vol. 9, no. 2, pp. 1003–1016, May. 2013.
• [14] Y. Zhang, Y. Bai, H. Yang and B. Zhang “Low switching frequency model predictive control of three-level inverter-fed im drives with speed-sensorless and field weakening operations,” IEEE Trans. Ind. Electron., vol. 66, no. 6, pp. 4262–4272, 2019, doi: 10.1109/TIE.2018.2868014.
• [15] S.A. Davari, D.A. Khaburi, and R. Kennel, “An improved FCSMPC algorithm for an induction motor with an imposed optimized weighting factor,” IEEE Trans. Power Electron., vol. 27, no. 3, pp. 1540–1551, 2012.
• [16] L. Yan, M. Dou, H. Zhang, and Z. Hua, “Speed sensorless dual reference frame predictive torque control for induction machines,” IEEE Trans. Power. Electron., vol. 34, no. 12, pp. 12285–12295, 2019, doi: 10.1109/TPEL.2019.2904542.
• [17] C.S. Vazquez, J. Rodriguez, M. Rivera, L.G. Franquelo, and M. Norambuena, “Model predictive control for power converters and drives: advanced and trends,” IEEE Trans. Ind. Electron., vol. 64, no. 2, pp. 935–947, 2017.
• [18] W. Xie et al., “Finite control set-model predictive torque control with a deadbeat solution for pmsm drives,” IEEE Trans. Ind. Electron., vol. 62, no. 9, pp. 5402–5410, Sept. 2015, doi: 10.1109/TIE.2015.2410767.
• [19] Y. Zhang, B. Yang, H. Yang, and M. Nurambuena, “Generalized sequential model predictive control of im drives with field-weakening ability,” IEEE Trans. Power Elecron., vol. 34, no. 9, pp. 8944–8955, 2019, doi: 10.1109/TPEL.2018.2886206.
• [20] M. Norambuena, J. Rodrigez, Z. Zhang, F. Wang, C. Garcia, R. Kenel, and G.-D. Andreescu, “A very simple strategy for high-quality performance of AC machines using model predictive control,” IEEE Trans. Power Electron., vol. 34, no. 1, pp. 794–800, Jan. 2019.
• [21] J. Rodriguez, R.M. Kennel, J.R. Espinoza, M. Trincado, C.A. Silva, and C.A. Rojas, “High performance control strategies for electrical drives: An experimental assessment,” IEEE Trans. Ind. Electron., vol.29, no. 2, pp. 812– 820, Jan/Feb. 2012.
• [22] T. Geyer, “Tuning guidelines for model predictive torque and flux control,” IEEE Trans. Ind. Appl., vol. 54, no. 5, pp. 4464–4475, Oct. 2018.
• [23] F. Wang, G. Lin, and Y. He, “Passivity-based model predictive control of three-level inverter-fed induction motor,” IEEE Trans. Power. Electron., vol. 36, no. 2, pp. 1984–1993, Feb. 2021, doi: 10.1109/TPEL.2020.3008915.
• [24] M. Pacas and J. Weber, “Predictive direct torque control for the PM synchronous machine,” IEEE Trans. Ind. Electron., vol. 52, no. 5, pp. 1350–1356, Oct. 2005.
• [25] F. Niu, F. Niu, K. Li, and Y. Wang, “Direct torque control for permanent-magnet synchronous machines based on duty ratio modulation,” IEEE Trans. Ind Electron., vol. 62, no. 10, pp. 6160–6170, Oct. 2015.
• [26] Y. Zhang and J. Zhu, “Direct torque control of permanent magnet synchronous motor with a reduced torque ripple and commutation frequency,” IEEE Trans. Power Electron., vol. 26, no. 1, pp. 235–248, Jan. 2011.
• [27] J.-K. Kang and S.-K. Sul, “New direct torque control of induction motor for minimum torque ripple and constant switching frequency,” IEEE Trans. Ind. Appl., vol. 35, no. 5, pp. 1076–1082, Sep/Oct. 1999.
• [28] K.K. Shyu, J.K. Lin, V.T. Pham, M.J. Yang, and T.W. Wang, “Global minimum torque ripple design for direct torque control of induction motor drives,” IEEE Trans. Ind Electron., vol. 57, no. 9, pp. 3148–3156, Sep. 2010.
• [29] Y. Ren, Z.Q. Zhu, and J. Liu, “Direct torque control of permanent-magnet synchronous machine drives with a simple duty ratio regulator,” IEEE Trans. Ind. Electron., vol. 61, no. 10, pp. 5249–5259, Oct. 2014.
• [30] Q. Liu and K. Hameyer, “Torque ripple minimization for direct torque control of pmsm with modified FSMPC,” IEEE Trans. Ind. Electron., vol. 52, no. 6, pp. 4855–4864, Aug. 2016.
• [31] Y. Zhang and H. Yang, “Torque ripple reduction of model predictive torque control of induction motor drives,” in Proc. Energy Convers. Congr. Expo., 2013, pp. 1176–1183.
• [32] Y. Zhang, H. Yang, and B. Xia, “Model predictive torque control of induction motor drives with reduced torque ripple,” IET Electr. Power Appl., vol. 9, no. 9, pp. 595–604, 2015.
• [33] Y. Zhang and H. Yang, “Model predictive torque control of induction motor drives with optimal duty cycle control,” IEEE Trans. Power Elecron., vol. 29, no. 12, pp. 6593–6603, Dec. 2014.
• [34] Y. Zhang and H. Yang, “Generalized two-vector-based Model-predictive torque control of induction motor drives,” IEEE Trans. Power Elecron., vol. 30, no. 7, pp. 6593–6603, Jul. 2015.
• [35] Y. Zhang, J. Zhu, and B. Xia, “A novel duty cycle control strategy to reduce both the torque and stator flux ripples for DTC of permanent-magnet synchronous motor drives with switching frequency reduction,” IEEE Trans. Power Electron., vol. 31, no. 5, pp. 3738–3753, May 2016.
• [36] C. Lascu and G.-D. Andreescu, “Sliding mode observer and improved integrator with dc-offset compensation for flux estimation in sensorless controlled induction motors,” IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 785–794, Jun. 2006.
• [37] P.H. Cortes, S. Kouro, B. La Rocca, R. Vargas, J. Rodrigues, J. Leon, S. Vazquez, and L. Franquelo, “Guidelines for weighting factors design in model predictive control of power converters and drives,” in Proc. IEEE ICIT, 2009, pp. 1–7.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).