Automated HF modelling of induction machines considering the effects of aging

The use of wide bandgap semiconductor devices, such as SiC and GaN MOSFETs, in high-frequency converters introduces new challenges for the design of electric drives. The very fast switching transient of which these devices are capable, in fact, can become a serious threat for the reliability of the entire system. Electromagnetic interferences due to the high dv/dt and di/dt, voltage reflections along the cable that cause overvoltage and ringing at the motor terminals, and large common-mode voltages that produce current circulation in the motor bearings are recognized as the major phenomena leading to premature failure of the drive. It is therefore important for designers to approach the problem from a system point of view, having the possibility to accurately model the system in the high-frequency domain to take appropriate measures to increase reliability. In this paper, an automated fitting procedure is proposed to identify the high-frequency model of an induction machine, which is based on using a genetic optimization algorithm to find the best rational approximation for the motor characteristics. A series of accelerated electrical aging tests have also been performed on the motors. The results are used iteratively in the proposed fitting procedure to obtain a time-varying model taking into account the aging progression.