The rainflow algorithm is one of the most commonly used tools for studying stress conditions of a wide variety of systems, including power electronics devices and electrochemical batteries. One of the main drawbacks of the algorithm is the trade-off between data compression and the loss of information when classifying the stress cycles into a finite amount of histogram bins. This paper proposes a novel approach for classifying the stress cycles by using fuzzy logic in order to reduce the quantization error of the traditional histogram-based analysis. The method is tested by comparing the accumulated damage estimations of two support-vector regression algorithms when trained with each type of cycle-counting procedure. NASA's randomized battery usage data set is used as source of stress data. A 50% error reduction was observed when using the fuzzy logic-based approach compared to the traditional one. Thus, the proposed method can effectively improve the accuracy of diagnosis algorithms without penalizing their performance and memory-saving features.

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and TOMISLAV DRAGIC ˇEVIC ´The increasing grid penetration of renewable energy generation, energy storage, and controllable electronic loads [e.g., electric vehicle (EV) chargers, motor drives, and electrolyzers) is making power electronic converters (PECs)-their controllable grid connection interfaces-omnipresent. Therefore, fleets of PECs are becoming key players not only in coordinating the generation and storage but also in unlocking the potential for flexibility within each load. In this article, we discuss how cloud-based platforms and edge devices can allow for interfacing PECs and advanced control algorithms. We present seven different study cases using our own developed cloud-based platform that demonstrate the smart coordination of PECs in a variety of prototypes and real-world solutions. Moreover, the capabilities of cloud and edge computing are highlighted throughout the article at large, effectively characterizing cloud-based control of fleets of PECs as an essential part of the future energy sector.

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