Optimal design of electric machine used in spacecraft by using fuzzy multi-objective particle swarm algorithm

Permanent magnet synchronous machines (PMSM) used in spacecraft must be able to control the magnet flux. For this purpose, in addition to the magnet, an excitation coil is placed on their rotor, which is widely used in control purposes. Reducing torque ripple and increasing the average torque are two important goals in the design of electric machines. In this paper, first the average torque and torque ripple for the PMSM in several cases are determined by numerical method. Then, analytical functions are obtained for them by using multilayer perceptron neural network. Fixed coefficients in the neural network are adjusted so that not only the errors for the training, test, validation, and total data, are very small but also the error for the test data is very close to the error for the training data. After that, by multi-objective fuzzy particle swarm optimization algorithm, the dimensions of the PMSM are determined in such a way that the torque ripple is minimum and the average value of torque is maximum. The determination of the optimal point at the pareto front will be determined by using the fuzzy maximum-minimum method. In this paper, numerical analysis is performed with Maxwell software and neural network, optimization and fuzzy are modeled by Matlab one.