This paper presents a review of advanced architectures based on the partial power processing concept, whose main objective is to achieve a reduction of the power processed by the converter. If the power processed by the converter is decreased, the power losses generated by the power converter are reduced, obtaining lower sized converters and higher system efficiencies. Through the review 3 different partial power processing strategies are distinguished: Differential Power Converters, Partial Power Converters and Mixed strategies. Each strategy is subdivided into smaller groups that entail different architectures with their own advantages and disadvantages. Also, due to the lack of agreement that exists in the sources around the naming of the different architectures, this paper seeks to stablish a nomenclature that avoids confusion when indexing this type of architectures. Regarding Partial Power Converters an extensive application oriented description is also developed. Finally, the main conclusions obtained through the review are presented.

This paper summarizes the main results and contributions of the MagNet Challenge 2023, an open-source research initiative for data-driven modeling of power magnetic materials. The MagNet Challenge has (1) advanced the stateof-the-art in power magnetics modeling; (2) set up examples for fostering an open-source and transparent research community; (3) developed useful guidelines and practical rules for conducting data-driven research in power electronics; and (4) provided a fair performance benchmark leading to insights on the most promising future research directions. The competition yielded a collection of publicly disclosed software algorithms and tools designed to capture the distinct loss characteristics of power magnetic materials, which are mostly open-sourced. We have attempted to bridge power electronics domain knowledge with state-of-the-art advancements in artificial intelligence, machine learning, pattern recognition, and signal processing. The MagNet Challenge has greatly improved the accuracy and reduced the size of data-driven power magnetic material models. The models and tools created for various materials were meticulously documented and shared within the broader power electronics community.

Automotive Original Equipment Manufacturers (OEMs) require varying levels of functionalities and model details at different phases of the electric vehicles (EV) development process, with a trade-off between accuracy and execution time. This article proposes a scalable modelling approach depending on the multi-objective targets between model functionalities, accuracy and execution time. In this article, four different fidelity levels of modelling approaches are described based on the model functionalities, accuracy and execution time. The highest error observed between the low fidelity (LoFi) map-based model and the high fidelity (HiFi) physics-based model is 5.04%; while, the simulation time of the LoFi model is ~10 ⁴ times faster than corresponding one of the HiFi model. A detailed comparison of all characteristics between multi-fidelity models is demonstrated in this paper. Furthermore, a dSPACE SCALEXIO Hardware-in-the-Loop (HiL) testbench, equipped with a minimal latency of $18\mu $ sec, is used for real-time (RT) model implementation of the EV’s HV DC/DC converter. The performance of the entire HiL setup is compared with the Model-in-the-Loop (MiL) setup and the highest RMSE is limited to 0.54 among the HiL and MiL results. Moreover, the accuracy (95.7%) of the passive component loss estimation is verified through the Finite Element Method (FEM) software model. Finally, the experimental results of a full-scale 30-kW SiC DC/DC converter prototype are presented to validate the accuracy and correlation between multi-fidelity models. It has been observed that the efficiency deviation between the hardware prototype and multi-fidelity models is less than 1.25% at full load. Furthermore, the SiC Interleaved Bidirectional Converter (IBC) prototype achieves a high efficiency of 98.4% at rated load condition.

Power electronic converters are essential in modern energy systems, facilitating efficient energy conversion in applications such as renewable energy, transportation, and industry. Power semiconductors are crucial to ensure reliability within these converters, often representing the weakest link in performance and durability. Failures in these devices can lead to costly downtime, decreased performance, and safety risks in demanding applications. This article provides a comprehensive analysis of the reliability challenges and solutions associated with power semiconductors, specifically focusing on silicon (Si) IGBTs and silicon carbide (SiC) MOSFETs. It examines key failure mechanisms, such as gate-oxide degradation and thermo-mechanical aging, at both the chip and package levels. Additionally, the article offers a market-oriented overview of standard power semiconductor packages and insights into current manufacturing trends and their implications for reliability. It also explores Active Thermal Control (ATC) techniques, such as gate voltage modulation, which can be implemented at the user level to mitigate stress-related failures. The findings intend to inform future researchers and developers, ensuring that power electronics systems can meet the increasing demand for reliable, efficient, and safe energy solutions.

Temperature is one of the key factors when working with lithium-ion battery modules due to its influence in safety, performance, and lifespan concerns in these devices. High working temperatures reduce the available capacity of each cell within the module after several cycles due to aging; nonuniform temperature distributions in the module lead to different aging processes in each cell, and thus it will be impossible to take advantage of all the energy available in the Li-ion storage system, because the most aged cell will limit the available energy. This paper is focused on the minimization of the maximum temperature gradient of a battery module for high depth of discharge applications to avoid different aging processes of the cells within the module. Voltage balancing is proposed as a solution for this purpose, and different strategies and their results are presented in this paper.