Search Results (326)

This study presents a modular battery charging system based on a DC–DC buck converter with proportional–integral (PI) control, developed to support hands-on learning in power electronics education. In response to the need for flexible experimental platforms, the system is designed to bridge theoretical concepts of power conversion and control with practical implementation. The proposed setup employs cascaded current and voltage control loops to achieve constant current (CC) and constant voltage (CV) charging modes, while its modular hardware architecture allows modification of key parameters such as inductance, capacitance, and circuit topology. The control algorithms are implemented on a microcontroller, and real-time data acquisition is integrated using the ThingSpeak platform for monitoring system behaviour. Experimental results show that the current control loop recovers to its reference value within approximately 6 ms under abrupt load variations, whereas the voltage control loop settles within approximately 15 ms, demonstrating stable closed-loop performance. In addition, the system successfully charges a 12 V lead-acid battery following a standard CC–CV charging profile. Overall, the proposed experiment kit provides an effective educational platform and a practical basis for further exploration of battery charging strategies and power converter control. Full article

Abnormal electrolyte levels can lead to failures in lead-acid batteries. The capacitive method, as a non-invasive liquid level inspection technique, can be applied to the nondestructive detection of electrolyte level abnormalities in lead-acid batteries. However, due to the high viscosity of sulfuric acid in lead-acid batteries, residual liquid films are easily adhered to the tube walls during rapid liquid level drops, resulting in significant dynamic measurement errors in capacitive methods. To eliminate dynamic measurement errors caused by residual liquid film adhesion, this study proposes a hybrid deep learning model—Poly-LSTM. This model combines polynomial feature generation with a Long Short-Term Memory (LSTM) network. First, polynomial features are generated to explicitly capture the complex nonlinear and coupling effects in the sensor inputs. Subsequently, the LSTM network processes these features to model their temporal dependencies. Finally, the time information encoded by the LSTM is used to generate accurate liquid level predictions. Experimental results show that this method outperforms other comparative models in terms of liquid level estimation accuracy. At a rapid drop rate of 0.12 mm/s, the average absolute error (MAE) is 0.5319 mm, the root mean square error (RMSE) is 0.7180 mm, and the mean absolute percentage error (MAPE) is 0.1320%. Full article

The automotive industry is under pressure to reduce greenhouse gas emissions. While the growth of electric vehicles is crucial, optimizing low-voltage batteries for conventional powertrain architecture (12–48 V) can help reduce carbon dioxide emissions. Currently, lithium iron phosphate (LFP) batteries dominate the low-voltage battery market due to their stability, safety, and ecological benefits as replacement to lead-acid. However, sodium-ion batteries (SIB) are emerging as a promising alternative to LFP, offering advantages in power, lifespan, cold temperature performance, integration, cost, material availability, and sustainability. These advantages of sodium-ion batteries make them a perfect candidate for fulfilling the requirements typically associated with 48 V applications as well. This contribution evaluates low-voltage SIB prototypes developed by the company IAV GmbH and its partners and explores their potential for automotive applications, aiming to share insights and assess future prospects. Full article

Lead-acid batteries (LAB) continue to be one of the most widely used energy storage technologies worldwide, especially in the automotive sector and in backup systems. However, their use is a significant source of lead and sulfuric acid pollution, with negative impacts on the environment and human health. This review analyzes the environmental and health effects of LAB manufacturing, use, and recycling, and evaluates sustainable alternatives through life cycle analysis. A search was conducted in the Multidisciplinary Digital Publishing Institute (MDPI), Science Direct, and Springer databases, yielding more than 247 documents, from which 84 technical and scientific articles were selected, mostly from the last five years, excluding duplicates and irrelevant texts or those in languages other than English. The results reveal that conventional pyrometallurgical processes release between 30 and 50 kg of lead fumes per ton processed, causing concentrations of up to 5000 mg/kg of Pb in soils near informal plants, exceeding international limits by more than 25 times. In contrast, closed-loop hydrometallurgical technologies reduce emissions by more than 70% and increase secondary lead recovery, making them an environmentally friendly option. It is concluded that the sustainability of the LAB system requires technological innovation, effective regulation, and extended responsibility within an eco-friendly circular economy model. Full article

The global adoption of solar-powered streetlights has grown significantly, driven by their cost-effectiveness and potential to reduce dependence on fossil fuels associated with conventional street lighting. Battery storage represents a substantial portion of the total capital cost in solar-powered streetlight systems. Therefore, selecting an efficient charge regulator is crucial to protect battery lifespan and reduce energy losses. In this context, the choice of an appropriate charge regulator plays a vital role in enhancing system reliability and overall performance. This study presents a practical approach for evaluating three commercially available 6 A-rated Pulse Width Modulation (PWM) solar charge regulators intended for recharging lead-acid batteries in a proposed 12 V off-grid solar photovoltaic (PV) street lighting system. The regulators were evaluated concurrently in separate circuits, each experiencing similar meteorological conditions, including similar temperature and solar irradiance. The measured data for each regulator were acquired using LabVIEW-based virtual instruments. The performance comparison was conducted using the Linear Regression Algorithm (LRA) to support decision-making. Based on the analysis, the most suitable PWM charge regulator was identified as the one offering the best charging performance due to low internal losses. Hence, solar battery charge regulators with identical load current ratings do not necessarily deliver equivalent charge/discharge performance. Full article

Deep-Cycle Lead-Acid Batteries (DCLA) are widely known in stationary applications such as backup power and off-grid systems. However, their faster capacity decline compared to emerging batteries limits their efficiency and lifespan. This research investigates the potential of ultrasonication to enhance the performance of DCLA by reducing sulfation and internal resistance, thereby improving capacity retention and state of health (SOH). A system-level MATLAB/Simulink model was created to simulate a photovoltaic (PV) system under three load conditions: constant, variable, and realistic load. An ultrasonic device operating at 1700 kHz was implemented during the charging phase, and simulations were conducted to evaluate systems before and after ultrasonication. State of charge (SoC) and battery voltage were performance measures over 31 days. The results showed that the ultrasonication system maintained an average SoC up to twice that of the control system (78.8% vs. 37.9%) and sustained a higher average voltage (13.2 V vs. 12.6 V). Under realistic light-load conditions, the test system retained energy better and had a 38.37% percentage improvement. These findings indicate that ultrasonic integration is a viable retrofitting strategy to improve DCLA operation, particularly for off-grid and renewable energy storage applications. Full article

Renewable energy sources, such as photovoltaic panels and wind turbines, are increasingly integrated into domestic systems to address energy scarcity, rising demand, and climate change. However, their intermittent nature requires efficient energy storage systems (ESS) for stability and reliability. This systematic review, conducted in accordance with PRISMA guidelines, aimed to evaluate the size and chemical composition of battery energy storage systems (BESS) in household renewable energy applications. A literature search was conducted in Scopus in August 2025 using predefined keywords, and studies published in English from 2015 onward were included. Exclusion criteria included book chapters, duplicate conference proceedings, geographically restricted case studies, systems without chemistry or size details, and those focusing solely on electric vehicle batteries. Of 308 initially retrieved records, 83 met the eligibility criteria and were included in the analysis. The majority (92%) employed simulation-based approaches, while 8% reported experimental setups. No formal risk-of-bias tool was applied, but a methodological quality check was conducted. Data were synthesized narratively and tabulated by chemistry, nominal voltage, capacity, and power. Lithium-ion batteries were the most prevalent (49%), followed by lead–acid (13%), vanadium redox flow (3.6%), and nickel–metal hydride (1.2%), with the remainder unspecified. Lithium-ion dominated due to high energy density, long cycle life, and efficiency. Limitations of the evidence include reliance on simulation studies, heterogeneity in reporting, and limited experimental validation. Overall, this review provides a framework for selecting and integrating appropriately sized and composed BESS into domestic renewable systems, offering implications for stability, efficiency, and household-level sustainability. The study was funded by the PNRR NEST project and Sapienza University of Rome Grant. Full article

This study presents a comparative techno-economic and environmental assessment of three leading stationary energy storage technologies: lithium-ion batteries, lead-acid batteries, and hydrogen systems (electrolyzer–tank–fuel cell). The analysis integrates Life Cycle Assessment (LCA) and Levelized Cost of Storage (LCOS) to provide a holistic evaluation. The LCA covers the full cradle-to-grave stages, while LCOS accounts for capital and operational expenditures, efficiency, and cycling frequency. The results indicate that lithium-ion batteries achieve the lowest LCOS (120–180 EUR/MWh) and high round-trip efficiency (90–95%), making them optimal for short- and medium-duration storage. Lead-acid batteries, though characterized by low capital expenditures (CAPEX) and high recyclability (>95%), show limited cycle life and lower efficiency (75–80%). Hydrogen systems remain costly (>250 EUR/MWh) and less efficient (30–40%), yet they demonstrate clear advantages for long-term and seasonal storage, particularly under scenarios with “green” hydrogen production and reduced CAPEX. These findings provide practical guidance for policymakers, investors, and industry stakeholders in selecting appropriate storage solutions aligned with decarbonization and sustainability goals. Full article

This paper proposes a battery emulator based on a bidirectional non-inverting buck-boost power electronics converter. With the capability of bidirectional operation, it can emulate both charging and discharging processes. The proposed emulator is controlled with the advanced I² dual current-mode control (I²DCMC) algorithm, combined with a feedforward control, which ensures fast and accurate tracking of the voltage and current characteristics of the batteries. The emulator is universal in terms of the various mathematical models of the batteries, which can be implemented in real time. It has no limitations regarding different battery types. Detailed analysis and the design procedure of the proposed battery emulator are presented. The performances of the emulator are validated with simulation and experimental results for three battery types: polymer Li-ion, conventional Li-ion, and lead–acid battery. Both steady and transient states are analyzed, especially transitions between charging and discharging phases. The possibility of simple time scaling of charging/discharging processes is successfully achieved and demonstrated, which is very important in making tests faster, with preserved battery characteristics. Considering its low-cost and user-friendly operation, the proposed emulator can be a good alternative to the real batteries in experimental tests of different power electronics systems. The prototype, which is developed for the experimental verification of the emulator, is designed for and limited to the research of lower power ratings systems of up to 100 W. It is suitable in education to easily demonstrate the behavior of the batteries in multiple scenarios in controlled laboratory conditions. Full article

Gamma-aminobutyric acid type A receptors (GABA_ARs) are pentameric ligand-gated ion channels essential for inhibitory neurotransmission in the central nervous system. Subtype-specific expression patterns of GABA_AR subunits underlie their diverse roles in regulating anxiety, motor function, and sedation. While non-selective GABA_AR positive allosteric modulators (PAMs), such as benzodiazepines, are clinically effective anxiolytic drugs, their non-selective activity across α1/2/3/5 subunit-containing GABA_ARs leads to sedation, cognitive impairment, and risk of dependence. To address this, we evaluated ENX-102, a novel GABA_AR PAM, which exhibits selectivity for α2/3/5 subunits. In rodents, ENX-102 demonstrated dose-dependent anxiolytic-like activity following acute and sub-chronic administration, without sedation. ENX-102 exhibited a dose-dependent quantitative electroencephalography (qEEG) spectral signature in rodents that was distinct from that of benzodiazepines. In a double-blind, placebo-controlled, multiple-ascending dose study in healthy human volunteers, ENX-102 was evaluated using the NeuroCart, a CNS test battery including saccadic peak velocity (SPV), adaptive tracking, pupillometry, body sway, the Bond and Lader Visual Analog Scale (VAS), the Visual Verbal Learning Task (VVLT), and qEEG. ENX-102 produced reductions in SPV that were indicative of central target engagement, with minimal effects on alertness and motor coordination, which is consistent with subtype-selective GABA_AR targeting. Notably, qEEG revealed increased β-band power and decreased δ- and θ-band activity, which were distinct from the spectral profile of non-selective PAMs, supporting translational alignment with preclinical findings. Across dose levels, ENX-102 was well tolerated and exhibited favorable pharmacokinetics. These results support further clinical development of ENX-102 as a next-generation GABA_AR subtype-selective anxiolytic drug. Full article

The growing penetration of renewable energy sources requires resilient microgrids capable of providing stable and continuous operation. Hybrid energy storage systems (HESS), which integrate hydrogen-based storage systems (HBSS), battery storage systems (BSS), and supercapacitor banks (SCB), are essential to ensuring the flexibility and robustness of these microgrids. Accurate modelling of these microgrids is crucial for analysis, controller design, and performance optimization, but the complexity of HESS poses a significant challenge: simplified linear models fail to capture the inherent nonlinear dynamics, while nonlinear approaches often require excessive computational effort for real-time control applications. To address this challenge, this study presents a novel state space model with linear variable parameters (LPV), which effectively balances accuracy in capturing the nonlinear dynamics of the microgrid and computational efficiency. The research focuses on a high-voltage DC bus microgrid architecture, in which the BSS and SCB are connected directly in parallel to provide passive DC bus stabilization, a configuration that improves system resilience but has received limited attention in the existing literature. The proposed LPV framework employs recursive linearisation around variable operating points, generating a time-varying linear representation that accurately captures the nonlinear behaviour of the system. By relying exclusively on directly measurable state variables, the model eliminates the need for observers, facilitating its practical implementation. The developed model has been compared with a reference model validated in the literature, and the results have been excellent, with average errors, MAE, RAE and RMSE values remaining below 1.2% for all critical variables, including state-of-charge, DC bus voltage, and hydrogen level. At the same time, the model maintains remarkable computational efficiency, completing a 24-h simulation in just 1.49 s, more than twice as fast as its benchmark counterpart. This optimal combination of precision and efficiency makes the developed LPV model particularly suitable for advanced model-based control strategies, including real-time energy management systems (EMS) that use model predictive control (MPC). The developed model represents a significant advance in microgrid modelling, as it provides a general control-oriented approach that enables the design and operation of more resilient, efficient, and scalable renewable energy microgrids. Full article

Floating photovoltaic (FPV) systems are promising for coastal aquaculture where reliable electricity is essential for pumping, oxygenation, sensing, and control. A sustainable FPV–storage hybrid tailored to monsoon-prone sites is developed, with emphasis on energy efficiency and structural resilience. The prototype combines dual-axis solar tracking with a spray-cooling and cleaning subsystem and an active wind-protection strategy that automatically flattens the array when wind speed exceeds 8.0 m/s. Temperature, wind speed, and irradiance sensors are coordinated by an Arduino-based supervisor to optimize tracking, thermal management, and tilt control. A 10 W floating module and a fixed-tilt reference were fabricated and tested outdoors in Penghu, Taiwan. The FPV achieved a 25.17% energy gain on a sunny day and a 40.29% gain under overcast and windy conditions, while module temperature remained below 45 °C through on-demand spraying, reducing thermal losses. In addition, a hybrid energy storage system (HESS), integrating a 12 V/10 Ah lithium-ion battery and a 12 V/24 Ah lead-acid battery, was validated using a priority charging strategy. During testing, the lithium-ion unit was first charged to stabilize the control circuits, after which excess solar energy was redirected to the lead-acid battery for long-term storage. This hierarchical design ensured both immediate power stability and extended endurance under cloudy or low-irradiance conditions. The results demonstrate a practical, low-cost, and modular pathway to couple FPV with hybrid storage for coastal energy resilience, improving yield and maintaining safe operation during adverse weather, and enabling scalable deployment across cage-aquaculture facilities. Full article

Auxiliary frequency modulation (FM) for coal-fired units has been recognized as a promising approach through multiple batteries, which is due to their rapid charging and discharging characteristics. However, long-period engineering application needs continuous optimization of operational strategies to resist the decay characteristics of the battery, which greatly increases the difficulty of promotion. Hence, two replacement strategies of the battery were first proposed in this work, and they are characterized by simple operation. To test their feasibility, a lead–acid battery was selected as one study example, and the corresponding relationship between the duration day and the replacement scheme was emphatically analyzed, according to the AGC instruction and the self-adjustment capacity of coal-fired units. Results showed that the replacement capacity of the battery is nearly linear in the duration day, while the difference from the discharge depth is negligible in this study. In addition, the capacity ratio of 1.3 to 5 is considered to have the best application potential because of the same duration days between old and new batteries. The commutative replacement can immortally extend the duration day, and obviously, the replacement process of old and new batteries always maintains that two battery groups work. Conclusively, the case analysis for two replacement strategies showed that they deeply lowered the initial capacity of the battery, which can reduce the investment costs. In a word, two replacement strategies for the battery proposed in this study provide a reference for the economic evaluation and optimization of battery use for auxiliary FM. Full article

The smart grid (SG) plays a seminal role in the modern energy landscape by integrating digital technologies, the Internet of Things (IoT), and Advanced Metering Infrastructure (AMI) to enable bidirectional energy flow, real-time monitoring, and enhanced operational efficiency. However, these advancements also introduce critical challenges related to data privacy, cybersecurity, and operational balance. This review critically evaluates SG systems, beginning with an analysis of data privacy vulnerabilities, including Man-in-the-Middle (MITM), Denial-of-Service (DoS), and replay attacks, as well as insider threats, exemplified by incidents such as the 2023 Hydro-Québec cyberattack and the 2024 blackout in Spain. The review further details the SG architecture and its key components, including smart meters (SMs), control centers (CCs), aggregators, smart appliances, and renewable energy sources (RESs), while emphasizing essential security requirements such as confidentiality, integrity, availability, secure storage, and scalability. Various privacy preservation techniques are discussed, including cryptographic tools like Homomorphic Encryption, Zero-Knowledge Proofs, and Secure Multiparty Computation, anonymization and aggregation methods such as differential privacy and k-Anonymity, as well as blockchain-based approaches and machine learning solutions. Additionally, the review examines pricing models and their resolution strategies, Demand–Supply Balance Programs (DSBPs) utilizing optimization, game-theoretic, and AI-based approaches, and energy storage systems (ESSs) encompassing lead–acid, lithium-ion, sodium-sulfur, and sodium-ion batteries, highlighting their respective advantages and limitations. By synthesizing these findings, the review identifies existing research gaps and provides guidance for future studies aimed at advancing secure, efficient, and sustainable smart grid implementations. Full article

Coriander is a significant crop, playing an essential role in daily life for various purposes, including flavouring curries and medicinal uses, among others. Despite its importance, coriander is still harvested manually. To address this, developed a self-propelled battery-operated coriander harvester, designed with ergonomics, environmental sustainability and affordability for small and marginal farmers in mind. The harvester is equipped with a main frame, a lead-acid battery, a BLDC motor, a reciprocating cutter bar, a PU conveyor belt, a collection bag, a handle, and transport wheels. The harvester was tested on the coriander crop, and the results were analyzed using Design Expert software to optimize various operational parameters. The harvester’s performance was evaluated at three forward speeds: 1.5 km/h, 2 km/h, and 2.5 km/h, resulting in covered areas of 0.114 ha, 0.164 ha, and 0.22 ha, with field efficiency values of 76%, 82%, and 88%, respectively. Optimal harvesting conditions were identified by design expert software at a forward speed of 1.64 km/h, with a conveyor driving pulley at level 3 (50.8 mm) and a cutting height at level 2 (75 mm). Under these conditions, the harvester achieved a harvesting efficiency of 97.24% and a cutting efficiency of 98.2%, with minimal conveying loss of 0.96%. The theoretical field capacity was 0.16 ha/h, the actual field capacity was 0.131 ha/h, and the overall field efficiency was 81.8%. Full article