International Journal of Advanced Innovative Technology in Engineering (IJAITE)

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Performance Analysis of Induction Motor Using Different Optimization Technique

Pankaj D. Bhuyar, Prof. C. M. Bobade

Abstract :

This paper aims to optimize the design of the induction motor to improve the performance in terms of efficiency, torque, and reduce the active material, which comprises the cost of the induction motor. Because the optimization of induction motor design is a highly nonlinear mix-discrete constrained multivariable problem, conventional optimization methods like golden section, Rosenbrok, Hooks, and Jeeves, are not effective. On the other hand, some optimization techniques like genetic algorithm, pattern search, simulated annealing, particle swarm, and interior point method are effective as they do not require derivative of the objective function to be optimized and are less time-consuming compared with a comparison with the standard nonlinear optimization methods. Thus, the following steps are adopted to achieve the objective: A 2.2 kW, 400 V, 1500 r.p.m., 3- phase squirrel cage induction motor is classically designed with a MATLAB program which is a generalized one, developed for motors ranging from 1 kW to 11kW. Using a genetic algorithm (GA) the classically designed motor is optimized thrice, once to get minimum active material cost than for maximum efficiency and finally for maximum full load torque. Keeping efficiency as the main objective function, pattern search (PS), simulated annealing (SA), interior-point (IP), and particle swarm (PSR) methods are used for maximizing efficiency. All the results obtained are then compared in a tabular form to suggest the best possible method for efficiency optimization.

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