Search Results (57)

This article presents the development, integration, and experimental validation of a modular microgrid for sustainable hydrogen production, addressing global electricity demand and environmental challenges. The system was designed for initial validation in a thermoelectric power plant environment, with scalability to other applications. Centered on a six-compartment skid, it integrates photovoltaic generation, battery storage, and a liquefied petroleum gas generator to emulate typical cogeneration conditions, together with a high-purity proton exchange membrane electrolyzer. A supervisory control module ensures real-time monitoring and energy flow management, following international safety standards. The study also explores the incorporation of blockchain technology to certify the renewable origin of hydrogen, enhancing traceability and transparency in the green hydrogen market. The experimental results confirm the system’s technical feasibility, demonstrating stable hydrogen production, efficient energy management, and islanded-mode operation with preserved grid stability. These findings highlight the strategic role of hydrogen as an energy vector in the transition to a cleaner energy matrix and support the proposed architecture as a replicable model for industrial facilities seeking to combine hydrogen production with advanced microgrid technologies. Future work will address large-scale validation and performance optimization, including advanced energy management algorithms to ensure economic viability and sustainability in diverse industrial contexts. Full article

We develop a modular, wireless, solar- and battery-powered system for detecting chlorpyrifos (Lorsban^TM 2.5% DP) in water using electrochemical impedance spectroscopy (EIS). The system integrates a Raspberry Pi Zero 2W for data processing, Python-based software (version 3.12.2), and a solar charge manager to power all components via a lithium-ion battery and solar panel. A commercial EmStat Pico Module and an amperometric biosensor with acetylcholinesterase (AChE) detect chlorpyrifos. Nine water samples with varying concentrations were tested using a 20 Hz–200 kHz frequency sweep and 15 mV excitation. Bode plots and statistical analyses confirmed statistically significant impedance variation as a function of chlorpyrifos concentration, validating the system as a portable, sensitive, and effective tool for environmental monitoring. Full article

The increasing adoption of electric vehicles (EVs) presents a growing demand for efficient, real-time battery monitoring systems. Many existing Battery Management Systems (BMS) with built-in Controller Area Network (CAN) communication are often expensive or lack user-friendly interfaces for displaying data. Moreover, integrating such BMS units with standard Human–Machine Interface (HMI) displays remains a challenge in cost-sensitive applications. This article presents the design and development of an interface for integrating the BMS of electric vehicles with the ATD3.5-S3 display using the CANopen protocol. The system enables the real-time visualization of essential battery parameters, including voltage, current, temperature, and state of charge (SOC) percentage. The proposed system utilizes a JK BMS, an ESP32 microcontroller, and a TJA1051 CAN transceiver to convert UART data into CAN Open messages. The design emphasizes affordability, modular communication, and usability in EV applications. Testing under various load conditions confirms the system’s stability, reliability, and suitability for practical use in electric vehicles. Full article

The continuous and reliable operation of autonomous systems is important for farm management decision making, whether such systems perform crop monitoring using imaging systems or crop handling in pruning and harvesting applications using robotic manipulators. Autonomous systems, including robotic ground vehicles, drones, and tractors, are major research efforts of precision crop management. However, these systems may be less effective or require specific customizations for planting systems in low tunnels, high tunnels, or other environmentally controlled enclosures. In this work, a compact and lightweight crop management platform is developed that uses overhead power cables for continuous operation over row crops, requiring less human intervention and independent of the ground terrain conditions. The platform does not carry batteries onboard for its operation, but rather pulls power from overhead cables, which it also uses to navigate over crop rows. It is developed to be modular, with the top section consisting of mobility and power delivery and the bottom section addressing a custom task, such as incorporating additional sensors for crop monitoring or manipulators for crop handling. This prototype illustrates the infrastructure, locomotive mechanism, and sample usage of the system (crop imaging) in the application of low-tunnel-covered strawberries; however, there is potential for other row crop systems with regularly spaced support structures to adopt this platform as well. Full article

This study shows a comprehensive simulation to assess and enhance the throughput capacity of unmanned air system vertiports, one of the most essential elements of urban air mobility ecosystems. The framework integrates dynamic grid-based spatial management, probabilistic mission duration algorithms, and EASA-compliant operational protocols to address the infrastructural and logistical demands of high-density UAS operations. It was focused on two use cases—high-frequency food delivery utilizing small UASs and extended-range package logistics with larger UASs—and the model incorporates adaptive vertiport zoning strategies, segregating operations into dedicated sectors for battery charging, swapping, and cargo handling to enable parallel processing and mitigate congestion. The simulation evaluates critical variables such as vertiport dimensions, UAS fleet composition, and mission duration ranges while emphasizing scalability, safety, and compliance with evolving regulatory standards. By examining the interplay between infrastructure design, operational workflows, and resource allocation, the research provides a versatile tool for urban planners and policymakers to optimize vertiport layouts and traffic management protocols. Its modular architecture supports future extensions. This work underscores the necessity of adaptive, data-driven planning to harmonize vertiport functionality with the dynamic demands of urban air mobility, ensuring interoperability, safety, and long-term scalability. Full article

Modular converters offer an effective solution for battery energy storage systems (BESSs) by lowering battery pack voltage levels and enabling additional functionalities, such as state of charge (SoC) and state of health (SoH) balancing, temperature regulation, and improved system reliability. However, conventional modular designs often require numerous additional components, including passive elements, switches, and sensing circuits. This paper proposes a modular multi-port converter (MMPC) BESS that combines energy conversion and battery management functions, leveraging the benefits of both modular and multi-port architectures. The proposed system demonstrates promising scalability and adaptability within the tested voltage and power ranges, with potential for extension to higher voltage and power applications through modular expansion. It also introduces an additional control layer, enhancing flexibility for control optimization and cost-effectiveness while improving reliability by reducing dependency on bypass switches. A prototype utilizing three dual-port converters managing six battery packs was developed. The experimental results confirm that the MMPC-based BESS achieves energy conversion and effectively balances the SoC among battery packs during both charging and discharging, under initial SoC mismatches. Full article

The increasing deployment of renewable energy sources is reshaping power systems and presenting new challenges for the integration of distributed generation and energy storage. Power converters have become essential to manage energy flows, coordinate storage systems, and maintain grid stability. This study presents a literature review following the PRISMA 2020 methodology, covering 71 peer-reviewed articles published between 2014 and 2024. The analysis organizes current research into five main areas: converter topologies, storage integration, grid interaction, advanced control strategies, and renewable energy applications. Recent developments include progress in multilevel and bidirectional converter designs, the use of wide-bandgap semiconductors (SiC, GaN), and the application of advanced control techniques such as model predictive control, fuzzy logic, and reinforcement learning. However, several challenges remain unresolved, including the lack of standardized validation protocols, limited implementation of modular and scalable converter solutions, and insufficient integration of hybrid storage technologies such as hydrogen and second-life batteries. Future efforts should focus on developing interoperable control platforms, extending field validation studies, and incorporating digital twins and AI-based supervisory systems to improve the reliability, efficiency, and scalability of converter-based energy storage solutions under high renewable energy scenarios. Full article

Multi-source systems are gaining attention as an effective approach to seamlessly incorporate renewable energies within electrical networks. These systems offer greater flexibility and better energy management possibilities. The considered multi-source system is based on a 50 MW wind farm connected to battery energy storage and electrolyzers through modular multi-level DC/DC converters. Wind energy systems interface with the DC-bus via rectifier power electronics that regulate the DC-bus voltage and implement optimal power extraction algorithms for efficient wind turbine operation. However, integrating intermittent renewable energy sources with optimal microgrid management poses significant challenges. It is essential to mention that the studied multi-source system is connected to the DC loads (modular electrolyzers and local load). This work proposes a new regulation method designed specifically to improve the performance of the system. In this strategy, the excess wind farm energy is converted into hydrogen gas and may be stored in the batteries. On the other hand, when the wind speed is low or there is no excess of energy, electrolyzer operations are stopped. The battery energy management depends on the power balance between the DC load (modular electrolyzers and local load) requirements and the energy produced from the wind farm. This control should lead to eliminating the fluctuations in energy production and should have a high dynamic performance. This work presents a nonlinear control method using a backstepping concept to improve the performances of the system operations and to achieve the mentioned goals. To evaluate the developed control strategy, some simulations based on real meteorological wind speed data using Matlab are conducted. The simulation results show that the proposed backstepping control strategy is satisfactory. Indeed, by integrating this control strategy into the multi-source system, we offer a flexible solution for battery and electrolyzer applications, contributing to the transition to a cleaner, more resilient energy system. This methodology offers intelligent and efficient energy management. Full article

This paper proposes a hybrid synchronization control modular multilevel converter-based hybrid energy storage system (HSC-MMC-HESS) that innovatively integrates battery units within MMC submodules (SMs) while connecting a supercapacitor (SC) to the DC bus. The configuration synergistically combines the high energy density of batteries with the high power density of SCs through distinct energy/power pathways. The operational principles and control architecture are systematically analyzed, incorporating a hybrid synchronization control (HSC) strategy to deliver system inertia, primary frequency regulation, fault-tolerant mode transition capabilities, and isolation control. A hierarchical control framework implements power distribution through filtering mechanisms and state-of-charge (SOC) balancing control for battery management. Hardware-in-the-loop experimental validation confirms the topology’s effectiveness in providing inertial support, enabling flexible operational mode switching and optimizing hybrid energy storage utilization. The demonstrated capabilities indicate strong application potential for medium-voltage distribution networks requiring dynamic grid support. Full article

Efficient and safe charging of lithium-ion batteries is essential for maximizing their lifespan and performance. This paper presents the design and implementation of a microcontroller-based Li-ion battery charger that employs real-time monitoring, adaptive charging strategies, and built-in safety mechanisms. The system integrates a CC/CV charging approach with automatic current regulation, overcharge protection, and reverse polarity detection. A current sensor module ensures continuous monitoring, while an LCD interface provides real-time feedback on charging parameters. Experimental validation was conducted using multiple Li-ion cells in various conditions, like new, aged, and deeply discharged, to evaluate charging behavior and safety under different scenarios. The system successfully regulated current and voltage, managed preconditioning for low-voltage cells, and transitioned smoothly between charging phases. A key contribution of this work is the development of a low-cost, microcontroller-based platform that enables flexible implementation and testing of diverse charging strategies. Its open-source architecture and modular design make it highly suitable for research, educational use, and experimental development in battery management systems. Future enhancements may include the integration of adaptive algorithms based on internal resistance and temperature, enabling smarter and more efficient charging. Full article

Gas evolution in lithium-ion batteries represents a pivotal yet underaddressed concern, significantly compromising long-term cyclability and safety through complex interfacial dynamics and material degradation across both normal operation and extreme thermal scenarios. While extensive research has focused on isolated gas generation mechanisms in specific components, critical knowledge gaps persist in understanding cross-component interactions and the cascading failure pathways it induced. This review systematically decouples gas generation mechanisms at cathodes (e.g., lattice oxygen-driven CO₂/CO in high-nickel layered oxides), anodes (e.g., stress-triggered solvent reduction in silicon composites), electrolytes (solvent decomposition), and auxiliary materials (binder/separator degradation), while uniquely establishing their synergistic impacts on battery stability. Distinct from prior modular analyses, we emphasize that: (1) emerging systems exhibit fundamentally different gas evolution thermodynamics compared to conventional materials, exemplified by sulfide solid electrolytes releasing H₂S/SO₂ via unique anionic redox pathways; (2) gas crosstalk between components creates compounding risks—retained gases induce electrolyte dry-out and ion transport barriers during cycling, while combustible gas–O₂ mixtures accelerate thermal runaway through chain reactions. This review proposes three key strategies to suppress gas generation: (1) oxygen lattice stabilization via dopant engineering, (2) solvent decomposition mitigation through tailored interphases engineering, and (3) gas-selective adaptive separator development. Furthermore, it establishes a multiscale design framework spanning atomic defect control to pack-level thermal management, providing actionable guidelines for battery engineering. By correlating early gas detection metrics with degradation patterns, the work enables predictive safety systems and standardized protocols, directly guiding the development of reliable high-energy batteries for electric vehicles and grid storage. Full article

The Monit4Healthy system is an IoT-enabled health monitoring solution designed to address critical challenges in real-time biomedical signal processing, energy efficiency, and data transmission. The system’s modular design merges wireless communication components alongside a number of physiological sensors, including galvanic skin response, electromyography, photoplethysmography, and EKG, to allow for the remote gathering and evaluation of health information. In order to decrease network load and enable the quick identification of abnormalities, edge computing is used for real-time signal filtering and feature extraction. Flexible data transmission based on context and available bandwidth is provided through a hybrid communication approach that includes Bluetooth Low Energy and Wi-Fi. Under typical monitoring scenarios, laboratory testing shows reliable wireless connectivity and ongoing battery-powered operation. The Monit4Healthy system is appropriate for scalable deployment in connected health ecosystems and portable health monitoring due to its responsive power management approaches and structured data transmission, which improve the resiliency of the system. The system ensures the reliability of signals whilst lowering latency and data volume in comparison to conventional cloud-only systems. Limitations include the requirement for energy profiling, distinctive hardware miniaturizing, and sustained real-world validation. By integrating context-aware processing, flexible design, and effective communication, the Monit4Healthy system complements existing IoT health solutions and promotes better integration in clinical and smart city healthcare environments. Full article

The evolution of aircraft power systems has been driven by increasing electrical demands and advancements in aviation technology. Background: This study provides a comprehensive review and experimental validation of on-board electrical network development, analyzing power management strategies in both conventional and modern aircraft, including the Mi-24 helicopter, F-22 multirole aircraft, and Boeing 787 passenger airplane. Methods: The research categorizes aircraft electrical systems into three historical phases: pre-1960s with 28.5 V DC networks, up to 2000 with three-phase AC networks (3 × 115 V/200 V, 400 Hz), and post-2000 with 270 V DC networks derived from AC generators via transformer–rectifier units. Beyond theoretical analysis, this work introduces experimental findings on hybrid-electric aircraft power solutions, particularly evaluating the performance of the Modular Power System for Aircraft (MPSZE). The More Electric Aircraft (MEA) concept is analyzed as a key innovation, with a focus on energy efficiency, frequency stability, and ground power applications. The study investigates the integration of alternative energy sources, including photovoltaic-assisted power supplies and fuel-cell-based auxiliary systems, assessing their feasibility for aircraft system checks, engine startups, field navigation, communications, and radar operations. Results: Experimental results demonstrate that hybrid energy storage systems, incorporating lithium-ion batteries, fuel cells, and photovoltaic modules, can enhance MEA efficiency and operational resilience under real-world conditions. Conclusions: The findings underscore the importance of MEA technology in the future of sustainable aviation power solutions, highlighting both global and Polish research contributions, particularly from the Air Force Institute of Technology (ITWL). Full article

The transition to a low-carbon energy matrix has driven the electrification of vehicles (EVs), yet charging infrastructure—particularly fast direct current (DC) chargers—can negatively impact distribution networks. This study investigates the integration of Battery Energy Storage Systems (BESSs) with the power grid, focusing on the E-Lounge project in Brazil as a strategy to mitigate these impacts. The results demonstrated a 21-fold increase in charging sessions and an energy consumption growth from 0.6 MWh to 10.36 MWh between June 2023 and March 2024. Compared to previous findings, which indicated the need for more robust systems, the integration of a 100 kW/138 kWh BESS with DC fast chargers (60 kW) and AC chargers (22 kW) proved effective in reducing peak demand, optimizing energy management, and enhancing grid stability. These findings confirm the critical role of BESSs in establishing a sustainable EV charging infrastructure, demonstrating improvements in power quality and the mitigation of grid impacts. The results presented in this study stem from a project approved under the Research and Development program of the Brazilian Electricity Regulatory Agency (ANEEL) through strategic call No. 022/2018. This initiative aimed to develop a modular EV charging infrastructure for fleet vehicles in Brazil, ensuring minimal impact on the distribution network. Full article

Battery parameter identification is a key challenge for battery management systems, as parameterizing lithium-ion batteries is resource-intensive. Electrical circuit models (ECMs) provide an alternative, but their parameters change with physical conditions and battery age, necessitating regular parameter identification. This paper presents two modular algorithms to improve data quality and enable fast, robust parameter identification. First, the dequantizer algorithm restores the time series generating the noisy, quantized data using the inverse normal distribution function. Then, the Linear Continuous-Time Regression (LCTR) algorithm extracts exponential parameters from first-order or overdamped second-order systems, deducing ECM parameters and guaranteeing optimality with respect to RMSE. The parameters have low sensitivity to measurement noise since they are continuous-time. Sensitivity analyses confirm the algorithms’ suitability for battery management across various Gaussian measurement noise, accuracy, time constants and state-of-charge (SoC), using evaluation metrics like root-mean-square-error (RMSE) (<2 mV), relative time constant errors, and steady-state error. If the coarseness of rounding is not extreme, the steady-state is restored within a fraction of a millivolt. While a slight overestimation in the lower time constants occurs for overdamped systems, the algorithms outperform the conventional benchmark for first-order systems. Their robustness is further validated in real-life applications, highlighting their potential to enhance commercial battery management systems. Full article