Induction Motor Design with Limited Harmonic Currents Using Particle Swarm Optimization
This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
[1] Z. Maljkovic, M. Cettolo, et.al, "The Impact of the Induction Motor on
Short-Circuit Current", IEEE Ind. Application Magazine, 2001, pp.
11-17.
[2] M. K. Yoon, C. S. Jeon, S. K. Kauh, "Efficiency Increase of an Induction
Motor by Improving Cooling Performance", IEEE Trans. Energy
Conversion, 2002, Vol. 17, pp. 1-6.
[3] M. Cacciato, A. consoli, G. Scarcella, G. Seelba, A. Testa, "Efficiency
optimization technique via constant optimal slip control of induction
motor drives", IEEE conference proceedings on Power Electronics,
Electric Drives, automation, and Motion, 2006, pp. 32-42.
[4] R. H. A. Hamid, A. M. A. Amin, R. S. Ahmed, A. El-Gammal, "New
Technique for Maximum Efficiency of Induction Motors Based on PSO",
IEEE conference proceedings, 2006, pp. 2176-2181.
[5] B. Pryymak, et al., "Neural Network based Flux Optimization using a
Model of Losses in Induction Motor Drives", Mathematics and computers
in simulation, Vol. 71, 2006, pp. 290-298.
[6] S. Lim, K. Nam., "Loss Minimization Control Scheme for Induction
Motors", IEE proc. Electr. Power appli., Vol. 151 No. 4, 2004, pp.
385-397.
[7] I. Kioskesidis, N. Margaris, "Loss minimization in scalar controlled
induction motor drives with search controller", IEEE Trans. Power
Electronics, Vol. 11, No. 2, 1996, pp. 213-220.
[8] C. Thanga Raj, Pramod Agarwal, , and S. P. Srivatava, "Particle Swarm
optimized Induction Motor for a Textile Mill Load Diagram", Proc. Of
IET Int. Conf. ICTES-07, India, Dec. 2007, pp. 379-383.
[9] S. Ghozzi , K. Jelassi, X. Roboam, "Energy Optimization of Induction
Motor Drives", IEEE conference on Industrial Technology (ICIT), 2004,
pp. 602-610.
[10] K. Sundareswaran et al., "Artificial Neural Network based Voltage
Controller for Energy Efficient Induction Motor Drives", IEEE Int.
Conference 1998.
[11] Jan Pawel Wieczorek, Ozdemir Gol, Z. Michalewicz, "An evolutionary
Algorithm for the Optimal Design of Induction Motors", IEEE Trans.
Magnetics, Vol. 34, No. 6, 1998.
[12] M. Cunkas, R. Akkaya, "Design Optimization of Induction Motor by
Genetic Algorithm and Comparison with Existiong Motor", Mathmatical
and Computational Applications, Vol. 11, No. 3. 2006, pp. 193-203.
[13] S. Padma, R. Bhuvaneswari, S. Subramanian, "Application of Soft
Computing Techniques to Induction Motor Design", Computation and
Mathematics in Elec. and Electronics Engg., Vol 26, No. 5, 2007, pp.
1324-1345.
[14] R. Bhuvaneswari, S. Subramanian, "Optimization of Three-Phase
Induction Motor Design using Simulated Annealing Algorithm", Electric
Power Components and Systems, Vol. 33, 2005, pp. 947-956.
[15] C. Thanga Raj, S. P. Srivastava, Pramod Agarwal, "Particle swarm
Optimized Design of Induction Motor with the consideration of
Unbalanced Supply Voltages, Int. J. of Mathematical Modeling,
Simulation and Applications, to be published.
[16] Bhim Singh, B. N. Singh, "Experience in the Design Optimization of a
Voltage Source Inverter Fed Squirrel Cage Induction Motor", Electric
Power Systems Research, Vol. 26, 1993, pp. 155-161
[17] Kennady, J and Eberhart. R, "Particle swarm optimization", IEEE
international conference on neural networks, NJ, 1995, PP. IV:
1942-1948.
[18] A. M. A. Amin, M. I. Korfally, a. A. Sayed, O. T. M. Hegazy, "Loss
minimization of two asymmetrical windings induction motor based on
swarm intelligence," IEEE conference proceedings, 2006, pp. 1156-1161.
[19] R. C. Eberhart, Y. Shi, "Comparing inertia weights and constriction
factors in particle swarm optimization", IEEE conference proceedings,
2000. pp 84-88.
[20] Fang Wang, Yuhui Qiu, "A modified particle swarm optimizer with
Roulette selection operator", IEEE conference proceedings of NLP-KE,
2005. pp 765-768.
[21] Millie Pant, Radha Thangaraj, Ajith Abraham, "A new Particle Swarm
Optimization Algorithm Incorporating Reproduction oPerator for Solving
Global Optimization Problem", Proc. of Hybrid Intelligent System (HIS),
IEEE Computer Society Press, 2007, pp. 144-149.
[22] R. Ramarathinam, B. G. Desai, "Optimization of Polyphase Induction
Motor Design: A Nonlinear Programming Aproach", IEEE Trans. Power
Apparatus and Systems, Vol. PAS-90, No. 2, Mar. / Apr. 1971, pp.
570-578.
[23] D. G. Bharadwaj, "Application of certain Optimization Techniques for
Cage Induction Machine", Ph.D Thesis, University of Roorkee, India,
1979.
[24] G. K. Dubey, "Power Semiconductor Controlled Drives", Prentice Hall,
New Jesey, 1989.
[1] Z. Maljkovic, M. Cettolo, et.al, "The Impact of the Induction Motor on
Short-Circuit Current", IEEE Ind. Application Magazine, 2001, pp.
11-17.
[2] M. K. Yoon, C. S. Jeon, S. K. Kauh, "Efficiency Increase of an Induction
Motor by Improving Cooling Performance", IEEE Trans. Energy
Conversion, 2002, Vol. 17, pp. 1-6.
[3] M. Cacciato, A. consoli, G. Scarcella, G. Seelba, A. Testa, "Efficiency
optimization technique via constant optimal slip control of induction
motor drives", IEEE conference proceedings on Power Electronics,
Electric Drives, automation, and Motion, 2006, pp. 32-42.
[4] R. H. A. Hamid, A. M. A. Amin, R. S. Ahmed, A. El-Gammal, "New
Technique for Maximum Efficiency of Induction Motors Based on PSO",
IEEE conference proceedings, 2006, pp. 2176-2181.
[5] B. Pryymak, et al., "Neural Network based Flux Optimization using a
Model of Losses in Induction Motor Drives", Mathematics and computers
in simulation, Vol. 71, 2006, pp. 290-298.
[6] S. Lim, K. Nam., "Loss Minimization Control Scheme for Induction
Motors", IEE proc. Electr. Power appli., Vol. 151 No. 4, 2004, pp.
385-397.
[7] I. Kioskesidis, N. Margaris, "Loss minimization in scalar controlled
induction motor drives with search controller", IEEE Trans. Power
Electronics, Vol. 11, No. 2, 1996, pp. 213-220.
[8] C. Thanga Raj, Pramod Agarwal, , and S. P. Srivatava, "Particle Swarm
optimized Induction Motor for a Textile Mill Load Diagram", Proc. Of
IET Int. Conf. ICTES-07, India, Dec. 2007, pp. 379-383.
[9] S. Ghozzi , K. Jelassi, X. Roboam, "Energy Optimization of Induction
Motor Drives", IEEE conference on Industrial Technology (ICIT), 2004,
pp. 602-610.
[10] K. Sundareswaran et al., "Artificial Neural Network based Voltage
Controller for Energy Efficient Induction Motor Drives", IEEE Int.
Conference 1998.
[11] Jan Pawel Wieczorek, Ozdemir Gol, Z. Michalewicz, "An evolutionary
Algorithm for the Optimal Design of Induction Motors", IEEE Trans.
Magnetics, Vol. 34, No. 6, 1998.
[12] M. Cunkas, R. Akkaya, "Design Optimization of Induction Motor by
Genetic Algorithm and Comparison with Existiong Motor", Mathmatical
and Computational Applications, Vol. 11, No. 3. 2006, pp. 193-203.
[13] S. Padma, R. Bhuvaneswari, S. Subramanian, "Application of Soft
Computing Techniques to Induction Motor Design", Computation and
Mathematics in Elec. and Electronics Engg., Vol 26, No. 5, 2007, pp.
1324-1345.
[14] R. Bhuvaneswari, S. Subramanian, "Optimization of Three-Phase
Induction Motor Design using Simulated Annealing Algorithm", Electric
Power Components and Systems, Vol. 33, 2005, pp. 947-956.
[15] C. Thanga Raj, S. P. Srivastava, Pramod Agarwal, "Particle swarm
Optimized Design of Induction Motor with the consideration of
Unbalanced Supply Voltages, Int. J. of Mathematical Modeling,
Simulation and Applications, to be published.
[16] Bhim Singh, B. N. Singh, "Experience in the Design Optimization of a
Voltage Source Inverter Fed Squirrel Cage Induction Motor", Electric
Power Systems Research, Vol. 26, 1993, pp. 155-161
[17] Kennady, J and Eberhart. R, "Particle swarm optimization", IEEE
international conference on neural networks, NJ, 1995, PP. IV:
1942-1948.
[18] A. M. A. Amin, M. I. Korfally, a. A. Sayed, O. T. M. Hegazy, "Loss
minimization of two asymmetrical windings induction motor based on
swarm intelligence," IEEE conference proceedings, 2006, pp. 1156-1161.
[19] R. C. Eberhart, Y. Shi, "Comparing inertia weights and constriction
factors in particle swarm optimization", IEEE conference proceedings,
2000. pp 84-88.
[20] Fang Wang, Yuhui Qiu, "A modified particle swarm optimizer with
Roulette selection operator", IEEE conference proceedings of NLP-KE,
2005. pp 765-768.
[21] Millie Pant, Radha Thangaraj, Ajith Abraham, "A new Particle Swarm
Optimization Algorithm Incorporating Reproduction oPerator for Solving
Global Optimization Problem", Proc. of Hybrid Intelligent System (HIS),
IEEE Computer Society Press, 2007, pp. 144-149.
[22] R. Ramarathinam, B. G. Desai, "Optimization of Polyphase Induction
Motor Design: A Nonlinear Programming Aproach", IEEE Trans. Power
Apparatus and Systems, Vol. PAS-90, No. 2, Mar. / Apr. 1971, pp.
570-578.
[23] D. G. Bharadwaj, "Application of certain Optimization Techniques for
Cage Induction Machine", Ph.D Thesis, University of Roorkee, India,
1979.
[24] G. K. Dubey, "Power Semiconductor Controlled Drives", Prentice Hall,
New Jesey, 1989.
@article{"International Journal of Electrical, Electronic and Communication Sciences:51228", author = "C. Thanga Raj and S. P. Srivastava and Pramod Agarwal", title = "Induction Motor Design with Limited Harmonic Currents Using Particle Swarm Optimization", abstract = "This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
", keywords = "Design, harmonics, induction motor, particle swarm optimization", volume = "2", number = "10", pages = "2162-7", }
