@article{(Open Science Index):https://publications.waset.org/pdf/8487,
	  title     = {Induction Motor Efficiency Estimation using Genetic Algorithm},
	  author    = {Khalil Banan and  Mohammad B.B. Sharifian and  Jafar Mohammadi},
	  country	= {},
	  institution	= {},
	  abstract     = {Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.
},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {1},
	  number    = {3},
	  year      = {2007},
	  pages     = {602 - 606},
	  ee        = {https://publications.waset.org/pdf/8487},
	  url   	= {https://publications.waset.org/vol/3},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 3, 2007},
	}