Zhang, Saeedifard Win IEEE Transactions on Power Electronics Top Paper Prize

<p>Yi Zhang (left) and Maryam Saeedifard</p>

Yi Zhang (left) and Maryam Saeedifard

Yi Zhang and Maryam Saeedifard won the first place prize paper award for 2020 in the IEEE Transactions on Power Electronics, one of the most impactful journals in the area of power electronics. Saeedifard is a professor in the Georgia Tech School of Electrical and Computer Engineering, and Zhang was a visiting Ph.D. student from Aalborg University who worked in Saeedifard’s research group in 2018-2019.

They will be presented with this award at the IEEE Energy Conversion Congress and Exposition, to be held October 10-14, 2021 in Vancouver, Canada. Being selected for this award is a high honor and a tribute to the fine research quality, presentation, and potential impact that the research has on the field. 

The paper entitled "Mission Profile-based System-level Reliability Prediction Method for Modular Multilevel Converters" was selected out of 1,148 papers published and some 13,000 papers that were submitted to the journal. The selection process for this prize paper was rigorous and went through multiple review levels and votes before the paper was selected for the award. This paper is also co-authored by Huai Wang and Frede Blaabjerg, who are both professors at Aalborg University in Denmark.

This paper proposes a mission profile-based reliability prediction method for modular multilevel converters (MMC), which have become the most promising technology in medium-and high-voltage applications. It includes key modeling steps, such as long-term mission profile, analytical power loss models, system-level and component-level thermal modeling, lifetime modeling, Monte Carlo analysis, and redundancy analysis. Thermal couplings and uneven thermal stresses among sub-modules are considered. A down-scale MMC has been used to demonstrate the proposed method and validate the theoretical analysis. The outcomes serve as a first step for developing realistic reliability analysis and model-based design methods for full-scale MMCs in practical applications.

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