Modeling and Analysis of PMSM with Turn-To-Turn Fault
Thanks to its high-torque density and high efficiency, the Permanent Magnet Synchronous Machine (PMSM) is today used in a vast range of applications, spanning from automotive to wind. Since in a PMSM the excitation field is provided by a permanent magnet instead of a coil, this machine does not have a rotor circuit and thereby the risk for electrical failures can be isolated on the stator circuit. These failures are mainly caused by the deterioration of the insulation of the winding due to, for example, thermal stress, electrical stress, mechanical stress, environmental issues or flaws from manufacturing. An insulation failure might lead to a short circuit between different parts of the machine; among these, the most common is the turn-to-turn short circuit. Even though the turn-to-turn fault typically only affects a small portion of the complete phase winding, the induced current in the faulted turns can exceed the rated one. This high current will produce excessive local heat, resulting in a rapid deterioration of the neighboring conductors’ insulation and thereby a reduction in the lifetime of the winding or, in the worst case, in permanent damage of the machine and the nearby components. It is therefore important to have good understanding of how a PMSM with turn-to-turn fault behaves in order to develop effective detection methods to limit the damage caused by the fault. This knowledge can be gained through proper modeling of the PMSM with turn-to-turn fault. This thesis focuses on the modeling of the PMSM with a turn-to-turn fault. Analytical models of the machine are derived and validated using Finite Element Method (FEM) models. The analytical model of the faulted PMSM is compared with the non-faulted machine model in order to understand the main characteristics and differences between the two conditions. Different quantities are considered as possible candidates for monitoring and detection of turn-to-turn faults. As first, the focus is on electrical quantities, especially the stator current. It is shown that the presence of a fault condition leads to an unbalance in the machine current and a variation in its harmonic spectra. However, it is shown that this variation is typically very small, posing a detectability issue for actual applications. The machine’s electrical power is a more effective signal for monitoring, as the signal incorporates variations in both voltage and current. If parallel windings are used, another possibility is to compare the different branch currents to detect the circulating current caused by the fault. Although it can be an effective detection method, it does require the availability of the branch current measurement in place of (or together with) the measurement of the phase current. An alternative way to identify a turn-to-turn fault is to monitor mechanical quantities. The impact of a turn-to-turn fault on the airgap flux density is limited to only a part of the airgap; as a result, the symmetrical distribution of the airgap flux density is lost in the event of a turn-to-turn fault. Thus, the fault will have an impact on both the electromagnetic tangential and radial force. For the non-faulted machine, the sum of the radial force in the airgap is zero; this does not apply for a faulted machine. The unbalance in radial force causes vibrations; the machine vibrations is the most effective quantity to monitor and used as a fault indication, as it is able to detect fault consisting of only a few short-circuited turns.
Permanent magnet synchronous machine (PMSM) modeling