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http://dx.doi.org/10.6113/TKPE.2019.24.1.33

SPMSM Mechanical Parameter Estimation Using Sliding-Mode Observer and Adaptive Filter  

Kim, Hyoung-Woo (Dept. of Electronics Engineering, Pusan National Univ.)
Choi, Joon-Young (Dept. of Electronics Engineering, Pusan National Univ.)
Publication Information
The Transactions of the Korean Institute of Power Electronics / v.24, no.1, 2019 , pp. 33-39 More about this Journal
Abstract
We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.
Keywords
Adaptive filter algorithm; Parameter estimation; SPMSM(Surface-mounted Permanent Synchronous Motor); SMO(Sliding Mode Observer);
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1 J. Davila, L. Fridman, and A. Poznyak, “Observation and identification of mechanical systems via second order sliding modes,” Int. J. Control, Vol. 79, No. 10, pp. 1251-1262, Oct. 2006.   DOI
2 J. Davila, L. Fridman, and A. Levant, “Second-order sliding-mode observer for mechanical systems,” IEEE Trans. Autom. Control, Vol. 50, No. 11, pp. 1785-1789, Nov. 2005.   DOI
3 X. Zhang and Z. Li, “Sliding mode observer-based mechanical parameter estimation for permanent-magnet synchronous motor,” IEEE Trans. Power Electron., Vol. 31, No. 8, pp. 5732-5745, Aug. 2016.   DOI
4 K. Liu and Z. Q. Zhu, “Online estimation of rotor flux linkage and voltage source inverter nonlinearity in permanent magnet synchronous machine drives,” IEEE Trans. Power Electron., Vol. 29, No. 1, pp. 418-427, Jan. 2014.   DOI
5 S. Kwak, U. C. Moon, and J. C. Park, “Predictive-controlbased direct power control with an adaptive parameter identification technique for improved AFE performance,” IEEE Trans. Power Electron., Vol. 29, No. 11, pp. 6178-6187, Nov. 2014.   DOI
6 T. H. Nguyen and D. C. Lee, “Deterioration monitoring of DC-link capacitors in AC machine drives by current injection,” IEEE Trans. Power Electron., Vol. 30, No. 3, pp. 1126-1130, Mar. 2015.   DOI
7 F. C. Dezza, G. Foglia, M. F. Iacchetti, and R. Perini, “An MRAS observer for sensorless DFIM drives with direct estimation of the torque and flux rotor current components,” IEEE Trans. Power Electron., Vol. 27, No. 5, pp. 2576-2584, May 2012.   DOI
8 H. Renaudineau, J. P. Martin, B. Nahid-Mobarakeh, and S. Pierfederici, “DC-DC converters dynamic modeling with state observer-based parameter estimation,” IEEE Trans. Power Electron., Vol. 30, No. 6, pp. 3356-3363, Jun. 2015.   DOI
9 H. Aung, K. S. Low, and S. Ting Goh, “State-of-charge estimation of lithium-ion battery using square root spherical unscented Kalman filter (Sqrt-UKFST) in nanosatellite,” IEEE Trans. Power Electron., Vol. 30, No. 9, pp. 4774-4783, Sep. 2015.   DOI
10 Y. Feng, X. Yu, and F. Hani, “High-order terminal sliding-mode observer for parameter estimation of a permanent-magnet synchronous motor,” IEEE Trans. Ind. Electron., Vol. 60, No. 10, pp. 4272-4380, Oct. 2013.   DOI
11 S. M. Yang and Y. J. Deng, "Observer-based inertia identification for auto tuning servomotor drives," in Proc. IEEE Conf. Rec. 40th Ind. Appl. Annu. Meet., pp. 968-972, 2005.