ization of Interior Permanent Magnet Synchronous using Genetic Algorithms

This paper presents an optimal design method to maximia the efficiency of the Interior Permanent Magnet Syn- chronous Motor. To do this, the efficiency of the motor is taken as the objective function, and the genetic algorithm is used as the optimization algorithm to find the optimal design variables of the objective function. To make the more accurate prediction of performance possible, the air gap flux density and d, q axis inductances obtained by an analytical method are compensated by using the results from finite element method. This paper presents a method suitable for the optimal de- sign of the Interior Permanent Magnet Synchronous Motors (IPMSMs). These motors have a promising application to the high power and high speed operations. But they have com- plex forms of performance formulas because of the rotor sa- liency structure as shown in Fig. l .( l) So most of the optimi- zation techniques based on the deterministic method can not be applicable to the optimal design of these kinds of motors which do not guarantee to find the global optimum. Recently, to overcome this difficulty, several stochastic methods are used which are proved to find the global optimum of the function. Among the widely used stochastic algorithms, ge- netic algorithm is used in this paper since the algorithm searches the global optimum faster than any other algorithms. In this paper, the efficiency of the motor is taken as the ob- jective function, and the values of design parameters that maximize the objective function are found. To obtain the more accurate performance formulas, the air gap flux density and d, q axis inductances are calculated from the equivalent