"Stator insulation degradation is one of the most common causes for failure in an electric machine. As wide bandgap device become more popular for inverter topologies, electrical stress increases and insulation failure becomes a more significant concern. Short circuits formed from degraded insulation can quickly lead to a catastrophic failure. A technique to detect when insulation is degraded, well before the formation of a short circuit, allows the machine to be safely powered-down. In this work, an online technique to detect insulation degradation and provide a failure prognosis is proposed. The proposed technique does not require high-frequency sampling or additional sensors as these requirements are costly. Accelerated thermal degradation of stator insulation is performed experimentally and the results show a trend in the measured current that can be used for prognosis. Inverter switching devices also degrade over their lifetime. A switching device that experiences gate oxide degradation produces features in the measured current that can mask changes due to insulation degradation. In this work, an online technique to detect gate oxide degradation in inverter switching devices is proposed. Accelerated gate oxide degradation of silicon and silicon-carbide MOSFETs shows that there are two features in the current that appear as the device degrades. Experimental results verify that one of the features in the current can be detected using steady-state voltage commands. Detecting degradation using quantities that are already calculated in the controller eliminates the need for additional sensor or high-frequency sampling. An algorithm to improve the robustness of the insulation failure prognosis is proposed. As gate oxide degradation can mask insulation degradation, it can also lead to an underestimation of remaining useful life. Also, as there are many sources of stress that degrade insulation, a change in the rate of degradation due to differences in applied stress or in the insulation system can significantly impact the insulation lifetime. The proposed technique improves robustness of the insulation failure prognosis by first separating between insulation and switching device degradation. Once it is determined that the insulation is degrading, the remaining useful life is predicted using the proposed algorithm that is robust to varying rates of degradation as well as variations in the insulation system. Data sets from experimental insulation degradation are used to compare the accuracy and robustness of the proposed stator insulation prognosis algorithm."--Pages ii-iii.
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