ABSTRACT
As described in Chapter 2, the ability to quantify the electromagnetic field and hence the electromagnetic force in an electric motor is essential to the prediction of acoustic noise from the motor. The process for predicting the acoustic field due to the operation of an electric motor can be illustrated in Figure 9.1. This process involves developing three models, namely, an electromagnetic model for estimating the electromagnetic force distribution in the motor, a structural model for describing the vibration behavior of the motor structure, and an acoustic model for predicting the acoustic response as a result of the electromagnetic excitation. All three models can be developed analytically. For example, the classical magneto-motive force and permeance wave theory has been used traditionally to analyze the distribution of the electromagnetic force in induction motors, and the effects of various parameters such as current harmonics, magnetic saturation, rotor eccentricity on its distribution. While the frequencies of harmonics due to different sources in the force spectrum could be clearly identified using the classical theory [31, 200, 248], it would be quite difficult to predict the magnitudes of these harmonics with accuracy. Analytical models can often provide good insight into the physics of acoustic noise generation. For example, by using an analytical approach, the lowest limit of the acoustic noise radiation for a variable speed induction motor can be determined [201]. With the advent of computer technology and numerical techniques, numerical methods such as the finite element method (FEM) have been widely used in modeling the detailed distribution of the electromagnetic force in the air gap, the vibration, and acoustic response of the motor structure [113, 153, 152, 163, 209, 232, 230, 246, 247, 252]. Numerical methods enable the assessment of the effects due to intricate structural details such as the tooth shape, slot depth, end shields, which cannot be otherwise made with analytical models.
