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Optimal Design of Motor using MPSO Algorithm

J. Furzana, J. Rizwana

Abstract


In many applications, efficiency of induction motors represents an important factor. So improving efficiency of three-phase squirrel cage induction motor can be achieved by selecting some optimum motor design parameters. The objective of this paper is to increase the efficiency of motor by minimizing the annual cost of the motor using MPSO. The objective function is a summation of the annual active material cost, annual power loss cost, annual energy loss cost. In the proposed MPSO algorithm, the parameters such as inertia weight and acceleration factors are introduced into the original PSO and made adaptive on the basis of objective function. By adapting the PSO parameters, it not only avoids premature convergence but also explores and exploits the promising regions in the search space successfully. The proposed method is applied to optimize the design of an industrial motor and the obtained results are compared with those of the conventional method to show their annual cost is minimized.

Keywords


Modified Particle Swarm Optimization (MPSO), Squirrel Cage Induction Motor, Optimum Motor Design, Annual Cost, Particle Swarm Optimization (PSO).

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References


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