Stator flux estimation with vector transforming and signal filtering method for electrical machines

Stator flux estimation with vector transforming and signal filtering method for electrical machines

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Stator flux estimation for electrical machine using voltage model (VM) with a simple structure and the least parameters has been widely researched in high-performance drive systems. Existing low-pass filter (LPF)-based estimators either respond slowly or cannot adequately suppress DC drifts, thus, a vector transforming and signal filtering method using VM is proposed for flux estimation. An original flux vector is directly produced through a transformation for motor back electromotive force, and then, the desired flux is obtained through an optimised filter which is designed by combing LPF and band-pass filter with an optimal function. The proposed estimator can both eliminate DC drifts and obtain a fast response and high accuracy, and additionally, its structure is simplified by the decomposing process, which significantly reduces the computation and occupied resources. The effects of cut-off frequencies on dynamical responses and flux harmonics are investigated and the limitations are obtained. This estimator is applicable to extensive strategies, for instance, the implementation of a direct torque control-based electrical drive system is carried out. Theoretical analysis, simulation, and experiment are conducted to validate the feasibility and effectiveness of the proposed scheme.


    1. 1)
      • 1. Gdaim, S., Mtibaa, A., Mimouni, M.F.: ‘Design and experimental implementation of induction machine based on fuzzy logic control on FPGA’, IEEE Trans. Fuzzy Syst., 2015, 23, (3), pp. 644655.
    2. 2)
      • 2. Sutikno, T., Idris, N.R.N., Jidin, A., et al: ‘An improved FPGA implementation of direct torque control for induction machines’, IEEE Trans. Ind. Inf., 2013, 9, (3), pp. 12801290.
    3. 3)
      • 3. Zhao, R.D., Xin, Z., Loh, P.C., et al: ‘A novel flux estimator based on multiple second-order generalized integrators and frequency-locked loop for induction motor drives’, IEEE Trans. Power Electron., 2017, 32, (8), pp. 62866296.
    4. 4)
      • 4. Marcetic, D.P., Krcmar, I.R., Gecic, M.A., et al: ‘Discrete rotor flux and speed estimators for high-speed shaft-sensorless IM drives’, IEEE Trans. Ind. Electron., 2014, 61, (6), pp. 30993108.
    5. 5)
      • 5. Koc, M., Sun, T.F., Wang, J.B.: ‘Performance improvement of direct torque controlled interior mounted permanent magnet drives by employing a linear combination of current and voltage based flux observers’, IET Power Electron., 2016, 9, (10), pp. 20522059.
    6. 6)
      • 6. Wang, K., Yao, W.X., Lee, K., et al: ‘Regenerating mode stability improvements for combined voltage and current mode flux observer in speed sensorless induction machine control’, IEEE Trans. Ind. Appl., 2014, 50, (4), pp. 25642573.
    7. 7)
      • 7. Suul, J.A., Luna, A., Rodriguez, P., et al: ‘Voltage-sensor-less synchronization to unbalanced grids by frequency-adaptive virtual flux estimation’, IEEE Trans. Ind. Electron., 2012, 59, (7), pp. 29102923.
    8. 8)
      • 8. Li, Y., Huang, W.X., Hu, Y.W.: ‘A low cost implementation of stator-flux-oriented induction motor drive’. Proc. 8th Int. Conf. Electrical Machines and Systems, 2005, vol. 2, pp. 15341538.
    9. 9)
      • 9. Smith, A.N., Gadoue, S.M., Finch, J.W.: ‘Improved rotor flux estimation at low speeds for torque MRAS-based sensorless induction motor drives’, IEEE Trans. Energy Convers., 2016, 31, (1), pp. 270282.
    10. 10)
      • 10. Wang, Y., Deng, Z.Q.: ‘Improvement stator flux estimation method for direct torque liner control of parallel hybrid excitation switched-flux generator’, IEEE Trans. Energy Convers., 2012, 27, (3), pp. 747756.
    11. 11)
      • 11. Hu, J., Wu, B.: ‘New integration algorithms for estimating motor flux over a wide speed range’, IEEE Trans. Power Electron., 1998, 13, (5), pp. 969977.
    12. 12)
      • 12. Comanescu, M., Xu, L.Y.: ‘An improved flux observer based on PLL frequency estimator for sensorless vector control of induction motors’, IEEE Trans. Ind. Electron., 2006, 53, (1), pp. 5056.
    13. 13)
      • 13. Patel, C., Ramch, R.J., Sivakumar, K., et al: ‘A rotor flux estimation during zero and active vector periods using current error space vector from a hysteresis controller for a sensorless vector control of IM drive’, IEEE Trans. Ind. Electron., 2011, 58, (6), pp. 23342344.
    14. 14)
      • 14. Singh, B., Jain, S., Dwivedi, S.: ‘Experimental investigation on flux estimation and control in a direct torque control drive’, Int. J. Adv. Eng. Technol., 2012, 4, (1), pp. 592599.
    15. 15)
      • 15. Luukko, J., Niemela, M., Pyrhonen, J.: ‘Estimation of the flux linkage in a direct-torque-controlled drive’, IEEE Trans. Ind. Electron., 2003, 50, (2), pp. 283287.
    16. 16)
      • 16. Alsofyani, I.M., Idris, N.R.N.: ‘Lookup-table-based DTC of induction machines with improved flux regulation and extended Kalman filter state estimator at low-speed operation’, IEEE Trans. Ind. Inf., 2016, 12, (4), pp. 14121425.
    17. 17)
      • 17. Comanescu, M.: ‘Design and implementation of a highly robust sensorless sliding mode observer for the flux magnitude of the induction motor’, IEEE Trans. Energy Convers., 2016, 31, (2), pp. 649657.
    18. 18)
      • 18. Comanescu, M.: ‘Single and double compound manifold sliding mode observers for flux and speed estimation of the induction motor drive’, IET Electr. Power Appl., 2014, 8, (1), pp. 2938.
    19. 19)
      • 19. Proca, A.B., Keyhani, A.: ‘Sliding-mode flux observer with online rotor parameter estimation for induction motors’, IEEE Trans. Ind. Electron., 2007, 54, (2), pp. 716723.
    20. 20)
      • 20. Xu, W., Lorenz, R.D.: ‘High-frequency injection-based stator flux linkage and torque estimation for DB-DTFC implementation on IPMSMs considering cross-saturation effects’, IEEE Trans. Ind. Appl., 2014, 50, (6), pp. 38053815.
    21. 21)
      • 21. Koc, M., Wang, J.B., Sun, T.F.: ‘An inverter nonlinearity-independent flux observer for direct torque-controlled high-performance interior permanent magnet brushless AC drives’, IEEE Trans. Power Electron., 2017, 32, (1), pp. 490502.
    22. 22)
      • 22. Liu, K., Zhu, Z.Q.: ‘Mechanical parameter estimation of permanent-magnet synchronous machines with aiding from estimation of rotor PM flux linkage’, IEEE Trans. Ind. Appl., 2015, 51, (4), pp. 31153125.
    23. 23)
      • 23. Xu, W., Lorenz, R.D.: ‘Reduced parameter sensitivity stator flux linkage observer in deadbeat-direct torque and flux control for IPMSMs’, IEEE Trans. Ind. Appl., 2014, 50, (4), pp. 26262636.
    24. 24)
      • 24. Moussa, M.A., Boucherma, M., Khezzar, A.: ‘A detection method for induction motor bar fault using sidelobes leakage phenomenon of the sliding discrete Fourier transform’, IEEE Trans. Power Electron., 2017, 32, (7), pp. 55605572.
    25. 25)
      • 25. Lyu, X.F., Li, Y.C., Cao, D.: ‘DC-link RMS current reduction by increasing paralleled three-phase inverter module number for segmented traction drive’, IEEE J. Emerg. Sel. Top. Power Electron., 2017, 5, (1), pp. 171181.
    26. 26)
      • 26. Takahashi, I., Noguchi, T.: ‘A new quick-response and high-efficiency control strategy of an induction motor’, IEEE Trans. Ind. Appl., 1986, IA-22, (5), pp. 820827.

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