Abstract
Monte Carlo simulation has been widely used for reliability assessment of power electronic systems. In this approach, multiple simulations are carried out during the lifetime estimation of the components in power converter, e.g., power devices, where the parameter variations are considered. In the previous mission-profile based reliability assessment methods, the dynamic thermal stress profiles are usually converted into a set of static parameters. However, this simplification may introduce a certain uncertainty during the reliability assessment, since the static parameters may not be able to accurately represent the thermal stress under highly dynamic conditions. Moreover, the previous research did not take into account the correlation between the method of introducing the parameter variation and the required number of Monte Carlo simulations. This can significantly affect both the accuracy and computation burden of the Monte Carlo simulation. To address this issue, an in-depth analysis of Monte Carlo simulation applied to reliability assessment of power devices in power electronic systems is provided in this paper. Two additional Monte Carlo simulation approaches based on semi-dynamic and dynamic parameters are proposed, and their reliability evaluation results are compared with the traditional static parameter method. It is demonstrated in a case study of photovoltaic (PV) inverter application that the reliability of power converter can be overestimated up to 30% when using the static parameters.
Highlights
P OWER electronic systems play an important role in enabling power conversion and control in several applications such as automotive, power supplies, and renewable energy systems [1]
If the lifetime model parameter variation is increased to 5% and 10% a difference in the unreliability curve of different Monte Carlo methods is more pronounced as it can be observed in Fig. 15 and Fig. 16, respectively
A comparison of three different Monte Carlo simulation methods used for reliability assessment of power electronic converters is presented in this paper
Summary
P OWER electronic systems play an important role in enabling power conversion and control in several applications such as automotive, power supplies, and renewable energy systems [1]. For a very high dynamic mission profile, e.g., due to load variations, a simple representation of all the dynamics of a power device junction temperature with one set of static parameters may introduce a certain error It has been demonstrated in [31] that different implementation methods of Monte Carlo simulation can affect the modelling accuracy. Compared to [31], where different methods of implementing parameter variations were presented on two application cases, the analysis in this paper is extended with a comprehensive guideline for parameter selection of Monte Carlo simulation to determine the minimum required number of simulation for a given parameter variation condition, and thereby minimize the computational burden of the analysis
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