Permanent Magnet Synchronous Motors (PMSMs) are increasingly being used and are required to satisfy noise and vibration specifications. Thus, it is necessary to develop design guidelines for electric motors that consider vibration response as a key output of the design. This work shows the influence of the main design parameters regarding PMSMs: the number of slots and the number of poles. First, the influence of the number of slots in the natural frequencies is analysed by Finite Element calculations, which are experimentally verified. Then, the analytical calculation of the vibration response is explained. This is applied for several combinations of the number of slots and the number of poles, and the results are compared. Considering the analytical development, a procedure to choose the most adequate combination of the number of slots and poles is proposed. The analytical predictions are validated according to experimental measurements in two machines.

The use of electric motors, and particularly, Permanent Magnet Synchronous Motors, is increasing in recent years, and their vibration response is one of the most crucial aspects regarding their behaviour. Thus, the reduction in vibrations is one of the key objectives when optimizing electric motors. In an initial design state, the influence of the main design parameters on the behaviour of the machines is not always clear. For that reason, this work presents a global sensitivity analysis procedure that allows identifying the most influential design parameters and determining guidelines to optimize the design of Permanent Magnet Synchronous Motors. First, the analytical calculations employed to estimate the electromagnetic torque and the vibration response of the machine are described. Then, the sensitivity analysis procedure, based on the Monte Carlo method, is presented, and the conditions to apply the method successfully and accurately are analysed. Finally, the sensitivity analysis is performed for a particular electric motor design, and some general design guidelines are deduced, which can be extrapolated to similar machines.

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