Structural optimisation of an induction motor using a genetic algorithm and a finite element method

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Doctoral thesis (monograph)
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Date

1996-08-27

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Department of Electrical and Communications Engineering
Sähkö- ja tietoliikennetekniikan osasto

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en

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99

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Acta polytechnica Scandinavica. El, Electrical engineering series, 84

Abstract

Several dozen variables affect the characteristics of an electric motor. The magnetic circuit of an electric motor is highly non-linear and analytically it is not possible to calculate the torque or losses in motors with sufficient accuracy for optimisation of the near air gap region. Only with the finite element method (FEM) is it possible to obtain sufficient accuracy. To be able to accurately evaluate the losses caused by higher harmonics the time-stepping method is needed to simulate the rotation of the rotor. The purpose of this work is to design and to test a method for structural optimisation and to use this method for the design of a new slot shape for induction motors, especially in the optimisation of the near air gap region. This method enables the design of more efficient and smaller motors, or vice versa, design of motors with a higher shaft power from the same amount of materials. This optimisation method is based on a genetic algorithm, and it is applied to the optimisation of the slot dimensions and the whole slot geometry with different voltage sources and optimisation constraints. In the genetic algorithm, optimisation is based on a population. The algorithm changes an entire population of designs instead of one single design in optimisation. The FEM is not accurate, i.e. all the changes in the mesh do not necessarily correspond real improvements in the characteristics of a motor. To improve the reliability of the optimisation results with FEM, the average design of the population is studied. The results obtained clearly indicate the usefulness and the effectiveness of both the optimisation method selected and the FEM in a design for induction motors.

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numerical simulation, finite element method, non-linear optimisation, genetic algorithm, structural optimisation, induction motor, slot shape, torque, electromagnetic losses

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https://urn.fi/urn:nbn:fi:tkk-001250

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[diss] Sähkötekniikan korkeakoulu / ELEC