1. Babel, A. S., J. G. Cintron-Rivera, S. N. Foster, et al. "Evaluation of a parameter identification method for permanent magnet AC machines through parametric sensitivity analysis," IEEE Transactions on Energy Conversion, Vol. 29, No. 1, 240-249, 2014.
doi:10.1109/TEC.2013.2288235        Google Scholar

2. Underwood, S. J. and I. Husain, "Online parameter estimation and adaptive control of permanent-magnet synchronous machines," IEEE Transactions on Industrial Electronics, Vol. 57, No. 7, 2435-2443, 2010.
doi:10.1109/TIE.2009.2036029        Google Scholar

3. Li, Z., G. Feng, C. Lai, D. Banerjee, W. Li, and N. C. Kar, "Investigation of on-line parameter estimation for interior PMSMs considering current injection and machine operating conditions," 2018 21th International Conference on Electrical Machines and Systems (ICEMS), 1395-1400, Jeju, Korea (South), 2018.        Google Scholar

4. Liu, K., Z. Q. Zhu, Q. Zhang, et al. "Influence of nonideal voltage measurement on parameter estimation in permanent-magnet synchronous machines," IEEE Transactions on Industrial Electronics, Vol. 59, No. 6, 2438-2447, 2012.
doi:10.1109/TIE.2011.2162214        Google Scholar

5. Rashed, M., P. F. A. MacConnell, A. F. Stronach, et al. "Sensorless indirect-rotor-field-orientation speed control of a permanent-magnet synchronous motor with stator-resistance estimation," IEEE Transactions on Industrial Electronics, Vol. 54, No. 3, 1664-1675, 2007.
doi:10.1109/TIE.2007.895136        Google Scholar

6. Liu, K. and Z. Q. Zhu, "Quantum genetic algorithm-based parameter estimation of PMSM under variable speed control accounting for system identifiability and VSI nonlinearity," IEEE Transactions on Industrial Electronics, Vol. 62, No. 4, 2363-2371, 2015.
doi:10.1109/TIE.2014.2351774        Google Scholar

7. Li, Z., G. Feng, C. Lai, et al. "Current injection-based multi-parameter estimation for dual three-phase IPMSM considering VSI nonlinearity," IEEE Transactions on Transportation Electrification, Vol. 5, No. 2, 405-415, 2019.
doi:10.1109/TTE.2019.2913270        Google Scholar

8. Yang, H., R. Yang, W. Hu, et al. "FPGA-based sensorless speed control of PMSM using enhanced performance controller based on the reduced-order EKF," IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol. 9, No. 1, 289-301, 2021.
doi:10.1109/JESTPE.2019.2962697        Google Scholar

9. Li, X. and R. Kennel, "General formulation of Kalman-filter-based online parameter identification methods for VSI-Fed PMSM," IEEE Transactions on Industrial Electronics, Vol. 68, No. 4, 2856-2864, 2021.
doi:10.1109/TIE.2020.2977568        Google Scholar

10. Liu, Z., H. Wei, X. Li, et al. "Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO," IEEE Transactions on Power Electronics, Vol. 33, No. 12, 10858-10871, 2018.
doi:10.1109/TPEL.2018.2801331        Google Scholar

11. Dos Santos Alonso, A. M., B. R. Pereira Junior, D. I. Brandao, et al. "Optimized exploitation of ancillary services: Compensation of reactive, unbalance and harmonic currents based on particle swarm optimization," Revista IEEE America Latina, Vol. 19, No. 2, 314-325, 2021.
doi:10.1109/TLA.2021.9443074        Google Scholar

12. Mahmud Ghasemi-Bijan, M. A. P. P., "Induction machine parameter range constraints in genetic algorithm based efficiency estimation techniques," IEEE Transactions on Industry Applications, Vol. 54, No. 5, 4186-4197, 2018.
doi:10.1109/TIA.2018.2836344        Google Scholar

13. Li, H. and L. Zhang, "A bilevel learning model and algorithm for self-organizing feed-forward neural networks for pattern classification," IEEE Transactions on Neural Networks and Learning Systems, Vol. 32, No. 11, 4901-4915, 2021.
doi:10.1109/TNNLS.2020.3026114        Google Scholar

14. Shen, Y. and B. Jin, "Parameter identification of permanent magnet synchronous motor by least square method with fuzzy forgetting factor," Journal of System Simulation, Vol. 30, No. 9, 3404-3410+3419, 2018.        Google Scholar

15. Mynar, Z., P. Vaclavek, and P. Blaha, "Synchronous reluctance motor parameter and state estimation using extended Kalman filter and current derivative measurement," IEEE Transactions on Industrial Electronics, Vol. 68, No. 3, 1972-1981, 2021.
doi:10.1109/TIE.2020.2973897        Google Scholar

16. Zhang, H., H. Yan, Y. Leng, and X. Wang, "Research on PMSM online identification based on model reference adaptation," Electric Drive, Vol. 45, No. 12, 3-7+16, 2015.        Google Scholar

17. Xiao, X., Q. Xu, Y. Wang, and Y. Shi, "A genetic algorithm-based method for parameter identification of embedded permanent magnet synchronous motor," Journal of Electrical Engineering Technology, Vol. 29, No. 3, 21-26, 2014.        Google Scholar

18. Gu, X., S. Hu, T. Shi, and Q. Geng, "Multi parameter decoupling online identification of permanent magnet synchronous motor based on neural network," Journal of Electrical Technology, Vol. 30, No. 6, 114-121, 2015.        Google Scholar

19. Shen, J., H. Yu, Y. Wang, M. Xu, and H. Chen, "Research on the application of standard particle swarm optimization algorithm in permanent magnet synchronous motor parameter identification," Micromotor, Vol. 48, No. 12, 32-35, 2015.        Google Scholar

20. Yuan, Y., "Parameter identification of permanent magnet synchronous motor based on adaptive particle swarm optimization algorithm," Measurement and Control Technology, Vol. 37, No. 7, 42-45+13, 2018.        Google Scholar

21. Lin, G., J. Zhang, C. Liu, and K. Zhao, "PMSM parameter identification with improved comprehensive learning particle swarm optimization algorithm," Journal of Electrical Machinery and Control, Vol. 19, No. 1, 51-57, 2015.        Google Scholar

22. Eberhart, R. and J. Kennedy, "A new optimizer using particle swarm theory," MHS'95, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 39-43, Nagoya, Japan, 1995.        Google Scholar