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A New Approach to Improve Induction Motor Performance in Light-Load Conditions

  • Hesari, Sadegh (Young Researcher and Elite Club, Bojnourd Branch, Islamic Azad University) ;
  • Hoseini, Aghil (Dept. of Electrical Engineering, Bojnourd Branch, Islamic Azad University)
  • Received : 2016.12.06
  • Accepted : 2017.02.17
  • Published : 2017.05.01

Abstract

Induction motors often reach their maximum efficiency at the nominal load. In most applications, the machine load is not equal to the nominal load, thus reduces the motor efficiency and turns a greater percent of power into loss. In this paper, the induction motor control problem has been investigated to reduce the system losses. The Field Oriented Control method (FOC) has been employed in this paper. In this research, the mathematical equations related to system losses are calculated in relation to torque and speed, and then the q- and d-axis are summarized according to the current components. After that, the proposed method is applied along with d- and q-axis. In the recent three decades, many techniques have been suggested to improve the induction motor performance using smart and non-smart methods. In this paper, a new PSO-Fuzzy method have used in real time. The fuzzy logic method serves as speed controller in q-axis and PSO algorithm controls the optimum flux in d-axis. It will be proved that the use of this combined method will lead to a significant improvement in motor efficiency.

Keywords

References

  1. M. Nasir Uddin, Sang Woo Nam, "New Online Loss-Minimization-Based Control of an Induction Motor Drive," IEEE Transactions on Power Electronics, vol. 23, no. 2, MARCH 2008.
  2. Sadegh Hesari, Mohsen Noruzi, Ali Asghar Shojaei, "Investigating the Intelligent Methods of Loss Minimization in Induction Motors," Hindawi publication, 2016.
  3. Rodrigo H. Cunha Palaciosa, Ivan N. da Silvaa, Alessandro Goedtel, "A novel multi-agent approach to identify faults in line connected three-phase induction motors," Applied Soft Computing Volume 45, August 2016, Pages 1-10. https://doi.org/10.1016/j.asoc.2016.04.018
  4. M. Ranjania, P. Murugesanb, "Optimal fuzzy controller parameters using PSO for speed control of Quasi-Z Source DC/DC converter fed drive," Applied Soft Computing vol. 27, February 2015, Pages 332-356. https://doi.org/10.1016/j.asoc.2014.11.007
  5. Rup Narayan Raya, Debashis Chatterjeeb, Swapan Kumar Goswami, "A PSO based optimal switching technique for voltage harmonic reduction of multilevel inverter," Expert Systems with Applications vol. 37, no. 12, December 2010, Pages 7796-7801. https://doi.org/10.1016/j.eswa.2010.04.060
  6. Sadegh Hesari, Mohammad Bagher Naghibi Sistani, "Optimizing the Deceased Induction Motor Losses using Genetic Algorithm," Majlesi Journal of Mechatronic Systems, vol. 4, no. 3, September 2015.
  7. Sadegh Hesari, Mohammad Bagher Naghibi Sistani, "Efficiency Improvement of Induction Motor using Fuzzy-Genetic Algorithm," International Journal of Smart Electrical Engineering, vol. 4, no. 2, Spring 2015.
  8. Navneet Kumar, Thanga Raj Chelliah, S. P. Srivastava, "Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives," ISA Transactions, vol. 57, July 2015, Pages 301-310. https://doi.org/10.1016/j.isatra.2015.02.011
  9. Eleftheria S. Sergaki, "Motor Flux Minimization Controller based on Fuzzy Logic Control for DTC AC Drives," International Conference on Electrical Machines-ICEM 2010, Rome.
  10. Shahriyar Kaboli, Mohammad Reza Zolghadri, "A Fast Flux Search Controller for DTC-Based Induction Motor Drives," IEEE Transaction on Industry Electronics, vol. 54, no. 5, October 2007.
  11. Dong Hwa Kima, Kaoro Hirota, "Vector control for loss minimization of induction motor using GAPSO," Applied Soft Computing, vol. 8, no. 4, September 2008, Pages 1692-1702. https://doi.org/10.1016/j.asoc.2006.09.001
  12. Chandan Chakraborty, and Yoichi Hori, "Fast Efficiency Optimization Techniques for the Indirect Vector-Controlled Induction Motor Drives," IEEE Transactions on Industry Applications, vol. 39, no. 4 pp. 1070-1076, July/August 2003. https://doi.org/10.1109/TIA.2003.814550
  13. Z. Rouabah, F. Zidani, B. Abdelhadi, "Efficiency optimization of induction motor drive using fuzzy logic and genetic algorithms," ISIE 2008, pp. 737-742, June 30-July 2 2008.
  14. J. Kennedy, R. C. Eberhart, "Particle swarm optimization," Proceedings of IEEE International Conference on Neural Networks," vol. 4, pp. 1942-1948, 1999.
  15. Sakuntala Mahapatra, Raju Daniel, Deep Narayan Dey, Santanu Kumar Nayak, "Induction Motor Control Using PSOANFIS," Elsevier, Procedia Computer Science 48 (2015), pp. 753-768. https://doi.org/10.1016/j.procs.2015.04.212
  16. V. P. Sakthivel, R. Bhuvaneswari, S. Subramanian, "Multi-objective parameter estimation of induction motor using particle swarm optimization," Engineering Applications of Artificial Intelligence vol. 23, no. 3, April 2010, Pages 302-312. https://doi.org/10.1016/j.engappai.2009.06.004
  17. Radwin H. A. Hamid, Amr M. A. Amin, Refaat S. Ahmed, and Adel A. A. El-Gammal, "New technique for maximum efficiency and minimum operating cost of induction motors based on particle swarm optimization," 32nd Annual Conference on IEEE Industrial Electronics, pp. 1029-1034, 2006.
  18. G. Sousa, "Application of Fuzzy Logic for Performance Enhancement of Drives," Phd Dissertation, Univ. of Tennessee, Knoxvilee, Dec. 1993.
  19. Venkatachalam M, Thangavel s, "Fuzzy Logic Based Performance Improvement of Induction Motor" 2012 IEEE International Conference on Engineering Education: Innovative Practices and Future Trends (AICERA), pp. 1-7, 19-21 July 2012.
  20. Ibrahim M. Alsofyani, , N. R. N. Idris, "A review on sensorless techniques for sustainable reliablity and efficient variable frequency drives of induction motors," Renewable and Sustainable Energy Reviews vol. 24, August 2013, Pages 111-121. https://doi.org/10.1016/j.rser.2013.03.051
  21. Jung-Sik Choi, Jae-Sub Ko, Ki-Tae Park, "High Performance Control of Induction Motor using GA," International Conference on Control, Automation and Systems 2007 Oct, 17-20, 2007 in COEX, Seoul, Korea.