Reliability Prediction and Assessment Models for Power Components: A Comparative Analysis

Reliability prediction and assessment play a significant role in determining the performance of power converter designs. Typically, the DC–DC power converters are one of the most required electronic components, and their reliability must be improved to increase the overall efficiency of the entire system. Usually, for power converters, the reliability is estimated using different standards such as MIL—HDBK, RIAC-217, Telcordia, IEC-TR-6238, and FIDES. This work aims to review the three main reliability assessment models (MIL—HDBK, RIAC-217, and FIDES) mainly used to validate the performance of DC-DC power converters. The advantages and disadvantages of each technique used in the DC-DC converter’s reliability design have been discussed and compared. We also presented an optimum assessment tool, which covers the fundamental factors for the reliability analysis of power converters. Furthermore, the reliability calculation tools like Markov, Monto Carlo and others are discussed with their significance in the reliability analysis of power converters. The inevitable part of the reliability study is the fault identification and diagnosis, which are elaborated with the methodologies reported in the literature for power converters. The importance of reliability study with respect to the application is briefly discussed. Finally, a comparative analysis of the various reliability statistical approaches would guide the researchers in choosing the appropriate methods for their reliability study. The principal objective behind this study is to propose a road map for power electronic engineers to perform the reliability study on DC–DC power converters.