PARAMETER ESTIMATION OF PERMANENT MAGNET SYNCHRONOUS MACHINES USING PARTICLE SWARM OPTIMIZATION ALGORITHM
Keywords:Particle swarm optimization toll, Permanent magnet synchronous machines, Permanent magnet synchronous machines equivalent circuit, Online parameters estimation
In this article, the particle swarm optimization toll (PSOT) is proceeded for solving the online parameters estimation of PMSM. The estimation procedure is depending on the real measurement of motor current and speed. The competitive algorithms are assessed in terms of the closeness between estimated and actual parameters’ which is considered the main target to be optimized in this work. Experimental verifications are carried out on Ecole Centrale de Nantes laboratories. The calculated results signify the effectiveness and reliability of the suggested tool. According to the results obtained, PSO has the capability and stability to calculate optimal values of PMSM parameters and then can calculate the performance of PMSM. The suggested PSO optimization tool leads to the highest closeness between estimated and experimental-based parameters. In addition, the POT is the outperformance optimization algorithm that gives the best values between the estimated and actual parameters.
(1) A. Khare, S. Shrivastava, Detailed modeling of permanent magnet synchronous motor for electrical forklifts part-III designing of permanent magnet synchronous motor dynamic model of permanent magnet synchronous motor block, Jea J. Electr. Eng., 2, 1, pp. 33–39 (2018).
(2) J.L. C. Lian, F. Xiao, S. Gao, load torque and moment of inertia identification for permanent magnet synchronous motor drives based on sliding mode observer,” IEEE Trans. Power Electron., 34, 6, pp. 5675–5683 (2019).
(3) L. Chretien, I. Husain, Position sensorless control of non-salient PMSM from very low speed to high speed for low-cost applications, Conf. Rec. - IAS Annu. Meet., IEEE Ind. Appl. Soc., pp. 289–296 (2007).
(4) D.V. Aparnathi, Modelling, simulation of permanent magnet synchronous machine drive using FOC technique, Glob. J. Res. Eng. Mech. Mech. Eng., 13, 9 (2013).
(5) A. Talha, B. El-Madjid, M.S. Boucherit, Study and control of two two-level PWM rectifier - clamping bridge-seven-level MPC VSI cascade: application to PMSM speed control, Eur. Trans. Electr. Power, 16, 1, pp. 93–107 (2006).
(6) A.K. Chakraboity, N. Sharma, Control of permanent magnet synchronous motor (pmsm) using vector control approach, Proc. IEEE Power Eng. Soc. Transm. Distrib. Conf., pp. 3–5 (July 2016).
(7) M. Tang, S. Zhuang, On speed control of a permanent magnet synchronous motor with current predictive compensation, Energies, 12, 1 (2019).
(8) X. Ding, S. Wang, M. Zou, M. Liu, Predictive current control for permanent magnet synchronous motor based on MRAS parameter identification, Proc. IEEE Int. Power Electronics and Application Conference and Exposition, PEAC, pp. 1–5 (2018).
(9) H. Ye, W. Song, Z. Ruan, Y. Yan, Current control methods for dual three-phase permanent magnet synchronous motors considering machine parameter asymmetry, 22nd International Conference on Electrical Machines and Systems, ICEMS, pp. 1–6 (2019).
(10) Y. Zhang, D. Xu, J. Liu, S. Gao, W. Xu, Performance improvement of model-predictive current control of permanent magnet synchronous motor drives, IEEE Trans. Ind. Appl., 53, 4, pp. 3683–3695 (2017).
(11) V.E. Kuznetsov, A.N. Lukichev, P.T. Chung, Speed control of permanent magnet synchronous motor with voltage surges reduction by means of adaptive control, Proc. IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus, pp. 590–594 (2019).
(12) F. Lin, S. Zuo, W. Deng, S. Wu, modeling and analysis of electromagnetic force, vibration, and noise in permanent-magnet synchronous motor considering current harmonics, IEEE Trans. Ind. Electron., 63, 12, pp. 7455–7466 (2016).
(13) M.K. Samat, A.A.A., Fazli, M.N., Salim, N.A., Omar, A.M.S. Osman, Speed control design of permanent magnet synchronous motor using Takagi- Sugeno fuzzy logic control, J. Electr. Syst., 13, 4, pp. 689–695 (2017).
(14) T. Guo, Z. Sun, X. Wang, S. Li, K. Zhang, A simple current-constrained controller for permanent-magnet synchronous motor, IEEE Trans. Ind. Informatics, 15, 3, pp. 1486–1495 (2019).
(15) Y. Miyama, M. Ishizuka, H. Kometani, and K. Akatsu, vibration reduction by applying carrier phase-shift PWM on dual three-phase winding permanent magnet synchronous motor, IEEE Trans. Ind. Appl., 54, 6, pp. 5998–6004 (2018).
(16) Z. Zhang, H. Wu, J. He, R. Chen, Development and verification of control algorithm for permanent magnet synchronous motor of the electro-mechanical brake booster, SAE Tech. Pap., pp. 1–11 (2019).
(17) X. Sun, Z. Shi, G. Lei, Y. Guo, J. Zhu, analysis and design optimization of a permanent magnet synchronous motor for a campus patrol electric vehicle, IEEE Trans. Veh. Technol., 68, 11, pp. 10535–10544 (2019).
(18) M.I. Abdelwanis, A. Abaza, R.A. El-Sehiemy, M. N. Ibrahim, H. Rezk, Parameter estimation of electric power transformers using coyote optimization algorithm with experimental verification, IEEE Access., 8, pp. 1–9 (2020).
(19) E.M. El-Sehiemy, R.A. Abd-Elwanis, M.I., Kotb, synchronous motor design using particle swarm optimization technique, proceedings of the 14th international middle east power systems, Conf. MEPCON’10, Cairo University, pp. 795–800 (2010).
(20) M. Abdelwanis, F. Selim, Optimal operation of synchronous motor using particle swarm optimization and jaya techniques, 21st Int. Middle East Power Systems Conf. (MEPCON), pp. 41–46 (2019).
(21) M.I. Abdelwanis, R.A. Sehiemy, M.A. Hamida, Hybrid optimization algorithm for parameter estimation of poly-phase induction motors with experimental verification, Energy AI, 5, 100083, pp. 1–15 (2021).
(22)W. Xu, M. M. Ismail, Y. Liu, M. R. Islam, Parameter optimization of adaptive flux-weakening strategy for permanent-magnet synchronous motor drives based on particle swarm algorithm, IEEE Trans. Power Electron., 34, 12, pp. 12128–12140 (2019).
(23) M.A. Sardarabadi, A.R., Hosseini, M. Noroozi, A new method for estimating permanent magnet synchronous machine parameters, J. Basic Appl. Sci. Res., 2, 9, pp. 9145–9151 (2012).
(24) S. Wang, Windowed least square algorithm based PMSM parameters estimation, Math. Probl. Eng., 2013 (2013).
(25) J. Long, M. Yang, Y.Q. Li, Y.Y. Chen, D.G. Xu, Parameter identification of permanent magnet synchronous motors: Sequence strategy comparative study, IEEE Transportation Electrification Conf. and Expo, Asia-Pacific, ITEC Asia-Pacific, pp. 3–5 (2017).
(26) D. Liang, J. Li, R. Qu, Super-twisting algorithm-based sliding-mode observer with online parameter estimation for sensorless control of permanent magnet synchronous machine, ECCE 2016 - IEEE Energy Conversion Congress and Expo, Proc., pp. 3–5 (2016).
(27) D. Yousri, M.B. Eteiba, A.F. Zobaa, D. Allam, Parameters identification of the fractional-order permanent magnet synchronous motor models using chaotic ensemble particle swarm optimizer, Appl. Sci., 11, 3, pp. 1–13 2021.
(28) A. Rahimi, F. Bavafa, S. Aghababaei, M. H. Khooban, S. V. Naghavi, The online parameter identification of chaotic behaviour in permanent magnet synchronous motor by self-adaptive learning bat-inspired algorithm, Int. J. Electr. Power Energy Syst., 78, pp. 285–291 (2016).
(29) M.S. Rafaq, F. Mwasilu, J. Kim, H.H. Choi, J.W. Jung, Online Parameter Identification for Model-Based Sensorless Control of Interior Permanent Magnet Synchronous Machine, IEEE Trans. Power Electron., 32, 6, pp. 4631–4643 (2017).
(30) A. Srivastava, D.K. Das, A. Rai, R. Raj, Parameter estimation of a permanent magnet synchronous motor using whale optimization algorithm, IEEE Int. Conf. on 2018 Recent Advances on Eng., Technolo. and Comput. Scie., RAETCS, pp. 1–6 (2018).
(31) A.J. Grobler, S.R. Holm, D.G. van Schoor, Empirical parameter identification for a hybrid thermal model of a high-speed permanent magnet synchronous machine, IEEE Trans. Ind. Electron., 65, 2, pp. 1616–1625 (2017).
(32) B. Jin, Y. Shen, D. Wu, Permanent magnet synchronous motor parameter identification with multi-innovation least squares, Proc. of the IEEE 11th Conference on Industrial Electronics and Applications, ICIEA, pp. 752–757 (2016).
(33) C.M. Ting, H.H. Chou, S. Cheng, Adaptive online parameters identification of nonlinear behavior in vector-controlled permanent magnet synchronous motors, IEEE Int. Conference on Mechatronics and Automation, ICMA, pp. 1384–1389 (2017).
(34) M.J. Khan, A.A. Kress, Identification of Permanent Magnet Synchronous Motor Parameters, SAE Tech. Pap., 2017-01–12, pp. 3–5 (2017).
(35) L.S. Maraaba, Z.M. Al-Hamouz, A.S. Milhem, S. Twaha, Comprehensive parameters identification and dynamic model validation of interior-mount line-start permanent magnet synchronous motors, Machines, 7, 1 (2019).
(36) H. Xu, Y. Xu, B. Cui, Study on on-line parameter identification of permanent magnet synchronous motor, J. Phys. Conf. Ser., 1087, 4 (2018).
(37) H. Zhang, W. Wu, L. Wang, An improved off-line identification technology for parameters of surface permanent magnet synchronous motors, 20th International Conference on Electrical Machines and Systems, ICEMS, pp. 3–5 (2017).
(38) P. Pramod, Z. Zhang, R. Mitra, S. Paul, R. Islam, J. Kleinau, Impact of parameter estimation errors on feedforward current control of permanent magnet synchronous motors, IEEE Transportation Electrification Conference and Expo, ITEC, pp. 3–5 (2016).
(39) Z. Liu, H. Wei, X. Li, K. Liu, Q. Zhong, Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO, IEEE Transactions on Power Electronics, 33, 12, pp. 10858-10871 (Dec. 2018).
(40) Z.-H. Liu, H.-L. Wei, Q.-C. Zhong, K. Liu, X.-S. Xiao, L.-H. Wu, Parameter estimation for VSI-Fed PMSM based on a dynamic PSO with learning strategies, IEEE Transactions on Power Electronics, 32, 4, pp. 3154-3165 (April 2017).
(41) Ali, Nihad et al. Optimization of the inductor of an induction cooking system using particle swarm optimization method and fuzzy logic controller, Rev. Roum. Sci. Techn. – Électrotechn. Et Énerg., 65, 3-4, pp. 185-190 (2020).
(42) A.A. Mekk, A. Kansa, M. Matallah, M. Feliachi, Nonlinear adaptive backstepping control of permanent magnet synchronous motor, Rev. Roum. Sci. Techn. – Électrotechn. Et Énerg., 66, 1, pp. 15-20 (2021).
(43) M. Slimane, D. Demba, A. Antoni, Mechanical sensor fault-tolerant controller in PMSM drive: experimental evaluation of observers and signal injection for position estimation, Rev. Roum. Sci. Techn. – Électrotechn. Et Énerg., 66, 2, pp. 77-83 (2021).
(44) R. Junior, E. Bermudes, O.E. Batista, D.S.L. Simonetti, differential analysis of fault currents in a power distribution feeder using abc, αβ0, and dq0 reference frames, Energies, 15, 2, pp. 526 (2022).
(45) T. Liu, G. Chen, S. Li, Application of vector control technology for PMSM used in electric vehicles, The Open Automation and Control Systems Journal, 6, 1, pp. 1334-1341 (2014).