Title :
Efficiency optimization of induction motors using genetic algorithm and Hybrid Genetic Algorithm
Author :
Tai, Yong ; Liu, Zhaomiao ; Yu, Huajin ; Liu, Jia
Author_Institution :
China Inst. of Atomic Energy, Beijing, China
Abstract :
Equivalent circuit model of induction motors was established and the formulas of power losses were given. Motor efficiency was optimized by Genetic Algorithm(GA) and Hybrid Genetic Algorithm(HGA). Power factor, breakdown torque ratio, locked-rotor torque ratio and locked-rotor current ratio were regarded as constraints and the optimal result is satisfying. Genetic Algorithm and Pattern Search Algorithm are integrated into a composite algorithm-Hybrid Genetic Algorithm. Motor efficiency rises further through Hybrid Genetic Algorithm.
Keywords :
equivalent circuits; genetic algorithms; induction motors; breakdown torque ratio; equivalent circuit model; hybrid genetic algorithm; induction motors; locked-rotor current ratio; locked-rotor torque ratio; motor efficiency; pattern search algorithm; power factor; power losses; Algorithm design and analysis; Genetic algorithms; Induction motors; Optimization; Rotors; Stators; Torque;
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1044-5
DOI :
10.1109/ICEMS.2011.6073854
