Open AccessGENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR
Author(s) -
Нго Фыонг Ле
Publication year - 2017
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2017-1-42-48
Subject(s) - computer science , genetic algorithm , process (computing) , synchronous motor , torque , electric motor , control engineering , reduction (mathematics) , engineering design process , optimization problem , permanent magnet synchronous motor , magnet , engineering , algorithm , mechanical engineering , mathematics , electrical engineering , physics , geometry , machine learning , thermodynamics , operating system
Classical method of designing electric motors help to achieve functional motor, but doesn’t ensure minimal cost in manufacturing and operating. Recently optimization is becoming an important part in modern electric motor design process. The objective of the optimization process is usually to minimize cost, energy loss, mass, or maximize torque and efficiency. Most of the requirements for electrical machine design are in contradiction to each other (reduction in volume or mass, improvement in efficiency etc.). Optimization in design permanent magnet synchronous motor (PMSM) is a multi-objective optimization problem. There are two approaches for solving this problem, one of them is evolution algorithms, which gain a lot of attentions recently. For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. This paper presents components and procedures of genetic algorithms, and its implementation on computer. In optimization process, analytical and finite element method are used together for better performance and precision. Result from optimization process is a set of solutions, from which engineer will choose one. This method was used to design a permanent magnet synchronous motor based on an asynchronous motor type АИР 112МВ 8.