The concept of the modular multilevel converter (MLC) has been raising interest in research in order to improve their performance and applicability. The potential of an MLC is enormous, with a great focus on medium- and high-voltage applications, such as solar photovoltaic and wind farms, electrified railway systems, or power distribution systems. This concept makes it possible to overcome the limitation of the semiconductors blocking voltages, presenting advantageous characteristics. However, the complexity of implementation and control presents added challenges. Thus, this paper aims to contribute with a critical and comparative analysis of the state-of-the-art aspects of this concept in order to maximize its potential. In this paper, different power electronics converter topologies that can be integrated into the MLC concept are presented, highlighting the advantages and disadvantages of each topology. Nevertheless, different modulation techniques used in an MLC are also presented and analyzed. Computational simulations of all the modulation techniques under analysis were developed, based on four cascaded full-bridge topologies. Considering the simulation results, a comparative analysis was possible to make regarding the symmetry of the synthesized waveforms, the harmonic content, and the power distribution in each submodule constituting the MLC.

Fabric defect detection is essential for quality assurance in textile manufacturing, where manual inspection is inefficient and error-prone. This paper presents a real-time deep learning-based system leveraging YOLOv11 for detecting defects such as holes, color bleeding and creases on solid-colored, patternless cotton and linen fabrics using edge computing. The system runs on an NVIDIA Jetson Orin Nano platform and supports real-time inference, Message Queuing Telemetry (MQTT)-based defect reporting, and optional Real-Time Messaging Protocol (RTMP) video streaming or local recording storage. Each detected defect is logged with class, confidence score, location and unique ID in a Comma Separated Values (CSV) file for further analysis. The proposed solution operates with two RealSense cameras placed approximately 1 m from the fabric under controlled lighting conditions, tested in a real industrial setting. The system achieves a mean Average Precision (mAP@0.5) exceeding 82% across multiple synchronized video sources while maintaining low latency and consistent performance. The architecture is designed to be modular and scalable, supporting plug-and-play deployment in industrial environments. Its flexibility in integrating different camera sources, deep learning models, and output configurations makes it a robust platform for further enhancements, such as adaptive learning mechanisms, real-time alerts, or integration with Manufacturing Execution System/Enterprise Resource Planning (MES/ERP) pipelines. This approach advances automated textile inspection and reduces dependency on manual processes.

Electric vehicles (EVs) are becoming increasingly popular due to their low emissions, energy efficiency, and reduced reliance on fossil fuels. One of the most critical components in an EV is the energy storage and management system, which requires compactness, lightweight, high efficiency, and superior build quality. Active cell equalization circuits such as those used in battery management systems (BMS) have been developed to balance the voltage and state of charge (SoC) of individual cells, ensuring the safety and reliability of the energy storage system. The use of these types of equalization circuits offers several benefits including improved battery performance, extended battery life, and enhanced safety, which are essential for the successful adoption of EVs. This paper provides a comprehensive overview of the research works related to active cell equalization circuits. This review highlights the important aspects, advantages and disadvantages, and specifications.

Rail power conditioner (RPC) has the ability to improve the power quality in AC railway power grids. This power conditioner can increase the loading capacity of traction substations, balance the active power between the feeder load sections, and compensate for reactive power and current harmonics. At present, there is increasing use of multilevel converter topologies, which provide scalability and robust performance under different conditions. In this framework, modular multilevel converter (MMC) is emerging as a prominent solution for medium-voltage applications. Serving that purpose, this paper focuses on the implementation, testing, and validation of a reduced-scale laboratory prototype of a proposed RPC based on an MMC. The developed laboratory prototype, designed to be compact, reliable, and adaptable to multipurpose applications, is presented, highlighting the main control and power circuit boards of the MMC. In addition, MMC parameter design of the filter inductor and submodule capacitor is also explained. Experimental analysis and validation of a reduced-scale prototype RPC based on MMC topology, are provided to verify the power quality improvement in electrified railway power grids. Thus, two experimental case studies are presented: (1) when both of the load sections are unequally loaded; (2) when only one load section is loaded. Experimental results confirm the RPC based on MMC is effective in reducing the harmonic contents, solving the problem of three-phase current imbalance and compensating reactive power.

This paper presents a single-phase Shunt Active Power Filter (SAPF) with a multilevel converter based on an asymmetric full-bridge topology capable of producing five distinct voltage levels. The calculation of the SAPF compensation current is based on the Generalized Theory of Instantaneous Reactive Power (p-q theory) modified to work in single-phase installations, complemented by a Phase-Locked Loop algorithm and by a dedicated algorithm to regulate the voltages in the DC-link capacitors. The control of the SAPF uses a closed loop predictive current control, followed by a multilevel Sinusoidal Pulse-Width Modulation technique with two vertical distributed carriers, which were specially conceived to deal with the asymmetric nature of the converter legs. Along the paper, some simulation results are used to show the main characteristics of the 5-level converter and control algorithms, and the hardware topology and control algorithms are described in detail. In order to demonstrate the feasibility and performance of the proposed SAPF based on a 5-level converter, a laboratory prototype was developed and experimental results obtained under diverse conditions of operation, with linear and non-linear loads, are presented and discussed in this paper.

This paper deals with the development and experimental validation of a unified power converter for application in dc microgrids, contemplating the inclusion of solar photovoltaic (PV) panels and energy storage systems (ESS), namely batteries. Considering the limitations presented by the current structure of the power grid, mostly highlighted by the accentuated integration of emerging technologies (ESS, renewables, electric vehicles, and electrical appliances that natively operate in dc), it is extremely pertinent to adopt new topologies, architectures, and paradigms. In particular, decentralized power systems, unified topologies, and correspondent control algorithms are representative of a new trend towards a reduction in the number of power converters. Thus, the developed solution is designed to operaSAVE-15te at a nominal power of 3.6 kW, with a switching frequency of 100 kHz, and in four operation modes concerning power flow: (i) solar PV panels to batteries (PV2B); (ii) solar PV panels to dc grid (PV2G); (iii) batteries to dc grid (B2G); (iv) dc grid to batteries (G2B). Moreover, a dual active bridge converter guarantees galvanic isolation, while two back-end dc–dc converters are responsible for interfacing solar PV panels and batteries. The experimental validation of the proposed unified power converter proves its application value to self-consumption production units.