Prediction and Validation of Wear-Out Reliability Metrics for Power Semiconductor Devices with Mission Profiles in Motor Drive Application

Due to the continuous demands for highly reliable and cost-effective power conversion, quantified reliability performances of the power electronics converter are becoming emerging needs. The existing reliability predictions for the power electronics converter mainly focus on the metrics of lifetime, accumulated damage, constant failure rate, or mean time to failure. Nevertheless, the time-varying and probability-distributed characteristics of the reliability are rarely involved. Moreover, in the public literatures, there are few evidences showing that the accuracy of the predicted reliability was experimentally validated. In this paper, a more advanced metric 'cumulative distribution function (CDF)' is introduced to predict the reliability performance of the power electronics system based on mission profiles in motor drive application. Furthermore, the accuracy of the predicted reliability metrics is verified through a series of wear-out tests in a converter testing system. It is concluded that the CDF is a very suitable metric to predict the reliability performance of the converter, and it has shown good accuracy with much more reliability information compared to the existing approaches. In this method, the correct stress translation and dedicated strength tests based on mission profiles are two key factors to ensure the efficiency and accuracy of reliability prediction.