Abstract

The article focuses on the use of genetic algorithms for the design of linear induction motors. Comparison of genetic algorithm with classical methods in the context of electrical machines designing has been carried out. The results of solving an optimization problem for two designs are presented, viz. a laboratory linear induction electric motor based on a three-phase SL-5-100 inductor and a traction single-sided linear induction electric motor of an urban transport system. The optimality criterion included maximizing the power factor and efficiency, as well as the rigidity of the mechanical characteristic while ensuring a starting traction force of at least a set value. The results of optimization of such parameters of the secondary element as the width and thickness of the conductive strip as well as the thickness of the magnetic circuit are described. The relevance of the problem of optimizing the parameters of the secondary element with unchanged parameters of the inductor is due to the fact that the same inductor can be used to build various structures, while the secondary element is created for each specific application and integrated directly into the working body of the mechanism or is a driven product. To calculate the traction and energy characteristics of linear induction electric motors, an electromagnetic model based on detailed equivalent circuits was used, taking into account longitudinal and transverse edge effects and providing a calculation time for one set of parameters of about 1 s. In accordance with this model, the electric motor is reduced to a set of three detailed equivalent circuits: a magnetic circuit, primary and secondary electrical circuits. The result of the optimization of these electric motors was an increase in the efficiency by 1.6 and 1.4 %, respectively, an increase in the power factor by 0.9 and 0.2 %, and an increase in the rigidity of traction characteristics and starting traction force.

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