Flux identification the rotor of six-phase induction motor using RBF neural network
Corressponding author's email:
trungnv@vlute.edu.vnDOI:
https://doi.org/10.54644/jte.64.2021.100Keywords:
Six-phase induction motor, Flux identification, RBF neural network, Dq axis, Multi input multi output systemsAbstract
Nowadays, six-phase induction motors are studied and applied because they have many advantages over traditional three-phase motors. This paper presents and simulates the rotor flux identification method on the dq axis of a six-phase induction motor using the identification tool as the RBF (Radial Basis Function) neural network. The RBF neural network is built and trained online based on input and output data of the motor. Simulation results using Matlab/Simulink software show that the error of the identification converges to 0 after a time of 0,002 seconds. The identification flux remains with the plant flux during engine starting and after loading. This study is a premise of progress to higher efficiency control methods such as FOC (Field Oriented Control), DTC (Direct Torque Control),...
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References
J. Ojeda, H.Bouker, L.Vido, H. Ben Ahmed, Comparison of 3-phase and 5-phase high speed synchronous motor for EV/HEV applications, Proc. IEEE Industry Applications Society Ann. Meeting IAS, pp.250–265, 2016. DOI: https://doi.org/10.1049/cp.2016.0271
M. Jones, S.N. Vukosavic, E.Levi, Experimental performance evaluation of six-phase series-connected two-motor drive systems, Proc. European Power Electronics and Applications Conf. EPE, pp.95–102, 2001.
Singh, G.K., and Pant, V., Analysis of a multiphase induction machine under fault condition in a phase-redundant AC drive system, Electr. Mach. Power Syst, 28 (6), pp. 577–590, 2000. DOI: https://doi.org/10.1080/073135600268199
Golubev, A.N., and Ignatenko, S.V., Influence of number of stator winding phases on the noise characteristics of an asynchronous motor, Russ. Electr. Eng., 71(6), pp. 41–46, 2000.
Williamson, S., and Smith, S., Pulsating torques and losses in multiphase induction machines, IEEE Trans. Ind. Appl., 39 (4), pp. 986–993, 2003. DOI: https://doi.org/10.1109/TIA.2003.813722
J. W. Finch and D. Giaouris, Controlled AC electrical drives, IEEE Trans. Ind.Electron, 55(2), pp. 481–491, 2008. DOI: https://doi.org/10.1109/TIE.2007.911209
G. Sheng-wei, Cai Yan, Design and Simulation of Flux Identification Based on RBF Neural Network for Induction Motor, ICCASM, pp. 273-277, 2010. DOI: https://doi.org/10.1109/ICCASM.2010.5619405
Huỳnh Thái Hoàng, Hệ thống điều khiển thông minh, 234-280, NXB ĐH Quốc gia TP. Hồ Chí Minh, 1, 2006.
M. S. Mandal, Performance Analysis of Six-Phase Induction Motor, IJERT, vol. 4, pp. 589–593, 2015.
Jinkun Liu, Rabias basis function (RBF) neural network control for mechanical systems design, Analysis and Matlab Simulation, Springer, 2013.
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