Passive Magnetic Bearings

The analysis of the behaviour of Passive Magnetic Bearing in order to achieve an acceptable magnetic force and stiffness is an interesting topic for rotating systems. Numerical analysis, which is an effective method to investigate the structural parameters of PMB, is applied using Finite Element Method to the two-dimensional model of Passive Magnetic Bearing. Numerical analysis is benefecial to predict the performances of the bearing versus differernt changes in the dimensions of the PMB. An optimization through Genetic Algorithms is then performed.The data gathered from the numerical analysis are therefore transferred to the Genetic Algorithm to facilitate the definition of the fitness and penalty functions which will help a faster convergence to the objective function. Providing a method to improve the magnetic force and consequently the magnetic stiffness of Passive Magnetic Bearings is an important purpose of this chapter. Also, in order to compare Passive Magnetic Bearing with different dimensions, the force to cost ratio is proposed as an index considering magnetic force and economical factors. The Genetic Algorithm is a stochastic optimization method which can be applied to reach the best dimensions according to the considered objective functions.