single-jc.php

JACIII Vol.20 No.7 pp. 1127-1134
doi: 10.20965/jaciii.2016.p1127
(2016)

Paper:

Demagnetization Faults Robust Detection Method Based on an Adaptive Sliding Mode Observer for PMSM

Changfan Zhang*, Miaoying Zhang**, Jing He*, Rui Shao**, and Lixiang Luo***

*Hunan University of Technology
No.188 Taishan Xi Road, Tianyuan District, Zhuzhou City, Hunan 412007, China
**Hunan Railway Professional Technology College
No.89 Tiandong Road, Shifeng District, Zhuzhou City, Hunan 412001, China
***China Power New Energy Dongguan Cogeneration Co., Ltd.
Tongxin Road, Dongcheng District, Dongguan City, Guangdong 523127, China

Received:
July 7, 2016
Accepted:
September 29, 2016
Online released:
December 20, 2016
Published:
December 20, 2016
Keywords:
permanent-magnet synchronous motor (PMSM), demagnetization faults, adaptive sliding mode observer
Abstract

To detect demagnetization faults in real time based on an adaptive sliding mode observer, we used a permanent-magnet synchronous motor (PMSM). Demagnetization faults are first modeled for the PMSM using coordinates oriented to the magnetic field. To solve demagnetization faults problems as multiple parameters change, we used adaptive and sliding mode variable structure control and designed an adaptive sliding mode observer. The adaptive estimation algorithm of the permanent magnet flux is given and the observer’s stability is proven by Lyapunov stability theory. Simulation and experimental results demonstrate the feasibility and effectiveness of our proposal.

References
  1. [1] J. He, C. F. Zhang, L. Jia, and K. H. Zhao, “Demagnetization fault reconstruction for permanent Magnet synchronous motor,” Electric Machines and Control, Vol.18, No.2, pp. 8-14, 2014.
  2. [2] D. Torregrossa, A. Khoobroo, and B. Fahimi, “Prediction of acoustic noise and torque pulsation in PM synchronous machines with static eccentricity and partial demagnetization using field Reconstruction method,” IEEE Trans. on Industry Applications, Vol.59, pp. 934-944, 2012.
  3. [3] G. Vinson, M. Combaca, and T. Prodo, “Permanent Magnets Synchronous Machines Faults Detection and Identification,” 38th Annual Conf. on IEEE Industrial Electronics Society, pp. 3925-3930, 2012.
  4. [4] A. R. Meghnous, M. T. Pham, and X. Lin Shi, “Dynamic Identification of a Synchronous Machine Using an Extended Sliding Mode Observer,” Mathematics and Computers in Simulation, Vol.90, pp. 45-59, 2013.
  5. [5] M. A. Hamida, A.Glumineau, J. Leon, and L. Loron, “Robust Adaptive High Order Sliding-mode Optimum Controller for Sensorless Interior Permanent Magnet Synchronous Motors,” Mathematics and Computers in Simulation, Vol.105, pp. 79-104, 2014.
  6. [6] K. H. Zhao, T. F. Chen, C. F. Zhang, J. He, and G. Huang, “Online Fault Detection of Permanent Magnet Demagnetization for IPMSMs by Non-singular Fast Terminal-Sliding-Mode Observer,” Sensors, Vol.14, No.12, pp. 23119-23136, 2014.
  7. [7] A. Tani, Y. Gritli, M. Mengoni, and L. Zarri, “Detection of magnet demagnetization and high-resistance connections in five-phase surface-mounted permanent magnet generators,” Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), 2015 IEEE 10th Int. Symp. on, Guarda, pp. 487-493, 2015.
  8. [8] C. F. Zhang, Z. Peng, X. F. Li, and J. He, “Robust demagnetization failure detection method based on adaptive observer,” J. of Electronic Measurement and Instrumentation, Vol.29, No.4, pp. 508-518, 2015 (in Chinese).
  9. [9] Y. M. Li and Y. Cai, “A New Adaptive Fuzzy Sliding Mode Control for Uncertain Nonlinear Systems,” Advanced Materials Research, Vol.327, pp. 12-16, 2011.
  10. [10] Y. L. Shu and Z. Y. Kong, “Adaptive Sliding Mode Variable Structure Control for a New Hyper Chaos System,” J. of Chongqing University of Technology (Natural Science), Vol.24, No.11, pp. 109-112, 2010.
  11. [11] Q. Du, Z. Su, and S. Li, “Some Design and Simulation of Sliding Mode Variable Structure Control for Hopf Bifurcation in Power Systems,” Energy and Power Engineering, Vol.3, pp. 24-28, 2011.
  12. [12] R. Kandiban and R. Arulmozhiyal, “Design of Adaptive Fuzzy PID Controller for Speed Control of BLDC Motor,” Int. J. of Soft Computing and Engineering, Vol.2, No.1, pp. 386-391, 2012.
  13. [13] H. Jin and J. Huang, “Adaptive Flux Estimation and Parameters Identification of Induction Motors Based on Model Reference Approach,” Trans. of China Electrotechnical Society, Vol.21, No.1, pp. 65-69, 2006 (in Chinese).
  14. [14] S. Abourida, C. Dufour, J. Belanger, and T. Yamada, “Hardware-in-the-loop simulation of finite-element based motor drives with RT-Lab and JMAG,” IEEE Int. Symp. on Industrial Electronics, pp. 2462-2466, 2006.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Mar. 27, 2017