Main Article Content

Abstract

In this paper, the carrier based Pulse Width Modulation (PWM) technique and neural network based rotor resistance estimator are proposed for vector controller Induction motor (IM) drives. The popular sine PWM is used for induction motor drive. The popular sine PWM has poor harmonic profile and (DC) utilization. The space vector modulation (SVM) technique overcomes the disadvantages of sine PWM. But SVM is computationally complex. Hence a simple PWM technique namely “carrier based PWM technique” similar to SVM is identified and proposed for vector controlled IM drive. The experimental set up is built up and the performance of carrier based PWM is validated using FPGA processor. The adaptive neural network based rotor resistance estimator in predictive mode is proposed for the vector controlled induction motor drive. The performance enhancement of the drive with carrier based PWM and rotor resistance estimator is comprehensively presented.

 

Keywords

Carrier based PWM technique Rotor resistance estimator MRAS Adaptive neural network Vector control Induction motor drive.

Article Details

How to Cite
A, V. (2019). CARRIER BASED PWM TECHNIQUE AND ADAPTIVE NEURAL NETWORK BASED ROTOR RESISTANCE ESTIMATOR FOR THE PERFORMANCE ENHANCEMENT OF VECTOR CONTROLLED INDUCTION MOTOR DRIVES. The Journal of Engineering Research [TJER], 16(1), 63–76. https://doi.org/10.24200/tjer.vol16iss1pp63-76

References

  1. Abdelkarim Ammar, Amor Bourek, Abdelhamid Benakcha (2017), Sensorless SVM-Direct torque control for induction motor drive using sliding mode observers. Journal of Control, Automation mand Electrical Systems 28(2): 189-201.
  2. Ahmed A.Z.D (2014), Real-time implementation of full-order observer for speed sensorless vector control of induction motor drive. Journal of Control. Automation and Electrical Systems 25 (6): 639-648.
  3. Beguenane R, Benbouzid M. E. H (1999), Induction motors thermal monitoring by means of rotor resistance identification. IEEE Transactions on Energy Conversion 14(3): 566-570.
  4. Benchabane F, Titaouine A, Bennis O, Yahia K, Taibi D (2012), Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor. Frontiers in Energy 6(2): 129-
  5. Bimal K. Bose (2005), Modern power electronics and AC drives. Prentice Hall of India.
  6. Chitra A, Himavathi S (2015), A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction motor drives. Frontiers in Energy 9(1): 22-30.
  7. Durgasukumar G, Pathak M.K (2012), Comparison of adaptive neuro-fuzzy-based space-vector modulation for two-level inverter. Electrical Power and Energy Systems 38: 9-19.
  8. Govindasamy Renukadevi, Kalyanasundaram Rajambal (2014), Field programmable gate array implementation of space-vector pulse-width modulation technique for five-phase voltage source inverter. IET Power Electronics 7(2): 376-389.
  9. Hannan M. A, Jamal Abd Ali, Azah Mohamed, Mohammad Nasir Uddin (2017), A random forest regression based space vector PWM inverter controller for the induction motor drive. IEEE Transactions on Industrial Electronics 64(4): 2689-2699.
  10. Karanayil B, Rahman M.F and Grantham C (2007), Online stator and rotor resistance estimation scheme using artificial neural networks for vector controlled speed sensorless induction motor drive. IEEE Transactions on Industrial Electronics 54 (1): 167-176.
  11. Keliang Zhou and Danwei Wang (2002), Relationship between space-vector modulation and three-phase carrier-based PWM: A comprehensive analysis. IEEE Transactions on Industrial Electronics 49 (1): 186-196.
  12. Krishnan R (2007), Electric motor drives modeling, analysis and control. Prentice Hall of India.
  13. Mahmoud Gaballah, Mohammed El-Bardini (2013), Low cost digital signal generation for driving space vector PWM inverter. Ain Shams Engineering Journal 4: 763-774.
  14. Maurizio Cirrincione, and Marcello Pucci (2005), An MRAS-based sensorless high-performance induction motor drive with a predictive adaptive model. IEEE Transactions on Industrial Electronics 52(2): 532-551.
  15. Peter Vas (1998), Sensorless vector and direct torque control. Oxford University Press.
  16. Sabah V.S, Charles Baby T, Krishna Prabhakar Lall, Balamurugan M,Sarat Kumar Sahoo, Chitra A,Prabhakar, Karthikeyan, I. Jacob Raglend (2015), A simplified space vector pulse width modulation technique for multilevel inverter fed induction motor drive. IEEE International Conference on Circuit, Power and Computing Technologies (ICCPCT).
  17. Shriwastava R.G, Daigavane M. B, Daigavane P. M (2016), Simulation analysis of three level diode clamped multilevel inverter fed PMSM drive using carrier based space vector pulse width modulation. (CB-SVPWM), Procedia Computer Science (Elsevier). 79: 616-623.
  18. Srirattanawichaikul W, Kumsuwan Y, Premrudeepreechacharn S, Wu B (2011), Carrier-based PWM strategy for three-level neutral-point-clamped voltage source inverters. IEEE PEDS 2011, Singapore, 948-951.
  19. Venkadesan A, Himavathi S and Muthuramalingam A (2016), A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector controlled IM drives. Frontiers in Energy 10(4): 382-392.
  20. Venkadesan A, Himavathi S, Sedhuraman K, Muthuramalingam A (2017), Design and field programmable gate array implementation of cascade neural network based flux estimator for speed estimation in induction motor drives. IET Electric Power Applications 11(1): 121-131.
  21. Witold P, Huynh V.K, Michael R.H (2017), Temperature rise estimation of induction motor drives based on loadability curves to facilitate design of electric powertrains. IEEE Transactions on Industrial Informatics 13(3): 985-994.