Search Results (1,643)

The increasing adoption of electric vehicles has driven the development of charging technologies that meet growing demands for power, efficiency, and grid compatibility. This review presents a comprehensive analysis of the EV charging ecosystem, covering Level 3 DC charging stations, power converter topologies, and the role of energy storage systems in supporting grid integration. Commercial solutions and academic prototypes are compared across key parameters such as voltage, current, power, efficiency, and communication protocols. The study highlights trends in charger architectures—including buck, boost, buck–boost, LLC resonant, and full-bridge configurations—while also addressing the integration of stationary storage as a buffer for fast charging stations. Special attention is given to wide-bandgap semiconductors like SiC and GaN, which enhance efficiency and thermal performance. A significant gap persists between the technical transparency of commercial systems and the ambiguity often observed in prototypes, highlighting the urgent need for standardized research reporting. Although converter efficiency is no longer a primary constraint, substantial challenges remain regarding infrastructure availability and the integration of storage with charging stations. This paper seeks to offer a comprehensive perspective on the design and deployment of smart, scalable, and energy-efficient charging systems, with particular emphasis on cascaded and bidirectional topologies, as well as hybrid storage solutions, which represent promising pathways for the advancement of future EV charging infrastructure. Full article

This paper presents a hybrid reinforcement learning framework for trajectory tracking control of a 5-degree-of-freedom (DOF) Mitsubishi RV-2AJ robotic arm by integrating model-free deep reinforcement learning (DRL) algorithms with classical control strategies. A novel hybrid PID + TD3 agent is proposed, combining a Proportional–Integral–Derivative (PID) controller with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, and is compared against standalone TD3 and PID controllers. In this architecture, the PID controller provides baseline stability and deterministic disturbance rejection, while the TD3 agent learns residual corrections to enhance tracking accuracy, robustness, and control smoothness. The robotic system is modeled in MATLAB/Simulink with Simscape Multibody, and the agents are trained using a reward function inspired by artificial potential fields, promoting energy-efficient and precise motion. Extensive simulations are performed under internal disturbances (e.g., joint friction variations, payload changes) and external disturbances (e.g., unexpected forces, environmental interactions). Results demonstrate that the hybrid PID + TD3 approach outperforms both standalone TD3 and PID controllers in convergence speed, tracking precision, and disturbance rejection. This study highlights the effectiveness of combining reinforcement learning with classical control for intelligent, robust, and resilient robotic manipulation in uncertain environments. Full article

This study investigates how trauma-informed and healing-centred architectural design is associated with rehabilitation and reintegration outcomes in young people’s correctional facilities. Drawing on international case studies, the analysis demonstrates that architecture is not a neutral backdrop but a contributing determinant within broader justice ecosystems. Trauma-informed environments are consistently linked to reductions in re-traumatisation and improvements in emotional regulation, while small-scale, community-oriented facilities are associated with enhanced skill development, autonomy, and reintegration potential. Culturally responsive designs that incorporate Indigenous practices and symbolic architecture are observed to support identity, resilience, and community belonging, underscoring the importance of cultural continuity in rehabilitation processes. In parallel, sustainable features such as biophilic design, renewable energy systems, and natural light are correlated with improvements in ecological performance and psychosocial well-being, indicating that sustainability and rehabilitation may be mutually reinforcing goals. Notably, the analysis highlights that supportive environments are also associated with staff well-being and institutional stability, underscoring the broader organisational benefits of healing architecture. The findings suggest that young people’s correctional facilities should not replicate adult prisons but instead provide safe, developmental, and culturally grounded spaces that respond to adolescents’ unique needs. This study contributes a novel conceptual model—the Trauma-Informed Healing Architecture (TIHA) framework—that integrates trauma-informed, cultural, and ecological design strategies within the Sustainable Development Goals (SDGs). The framework defines global standards as universal principles—safety, dignity, cultural responsiveness, and natural light—while remaining adaptable to local resources and justice systems. In this way, it provides internationally relevant yet context-sensitive guidance for young people’s correctional reform. Full article

To address the collaborative optimization challenge in multi-microgrid systems with significant renewable energy integration, this study presents a dual-layer optimization model incorporating power-hydrogen coupling. Firstly, a hydrogen energy system coupling framework including photovoltaics, storage batteries, and electrolysis hydrogen production/fuel cells was constructed at the architecture level to realize the flexible conversion of multiple energy forms. From a modeling perspective, the upper-layer optimization aims to minimize lifecycle costs by determining the optimal sizing of distributed PV systems, battery storage, hydrogen tanks, fuel cells, and electrolyzers within the microgrid. At the lower level, a distributed optimization framework facilitates energy sharing (both electrical and hydrogen-based) across microgrids. This operational layer maximizes yearly system revenue while considering all energy transactions—both inter-microgrid and grid-to-microgrid exchanges. The resulting operational boundaries feed into the upper-layer capacity optimization, with the optimal equipment configuration emerging from the iterative convergence of both layers. Finally, the actual microgrid in a certain area is taken as an example to verify the effectiveness of the proposed method. Full article

The rapid growth of electric vehicle (EV) adoption in Malaysia is projected to generate substantial volumes of end-of-life lithium-ion batteries, creating both environmental challenges and opportunities for repurposing into second-life batteries (SLBs). This study investigates the technical, economic, and regulatory feasibility of deploying SLBs for photovoltaic (PV) energy storage in petrol stations, an application aligned with the nation’s energy transition goals. Laboratory testing of Nissan Leaf ZE0 battery modules over a 120-day operation period demonstrated stable cycling performance with approximately 7% capacity fade, maintaining state-of-health (SOH) above 47%. A case study of a 12 kWp PV–SLB hybrid system for a typical Malaysian petrol station shows 45 kWh of usable storage, capable of offsetting a daily electricity demand of 45 kWh, reducing capital cost by 30–50% compared to new lithium-ion systems, and achieving 70–80% lifecycle CO₂ emission reductions. The proposed architecture leverages SLBs’ suitability for slower, steady discharge to provide reliable nighttime operation and grid load relief, particularly in semi-urban and rural stations. Beyond technical validation, the paper evaluates economic benefits, environmental impacts, and Malaysia’s regulatory readiness, identifying gaps in certification standards, reverse logistics, and workforce skills. Strategic recommendations are proposed to enable large-scale SLB deployment and integration into hybrid PV–petrol station systems. Findings indicate that SLBs can serve as a cost-effective, sustainable energy storage solution, supporting Malaysia’s National Energy Transition Roadmap (NETR), advancing circular economy practices, and positioning the country as a potential ASEAN leader in battery repurposing. Full article

Architectural exterior wall coatings require a balance of elasticity, stain resistance, and durability. Although nano-SiO₂ enhances fracture resistance in elastic coatings, its limited hydrophobicity allows pollutant adhesion. Nano-TiO₂ can photocatalytically degrade organics but is often encapsulated by the polymer matrix, reducing its effectiveness. This study introduces a SiO₂-TiO₂ composite topcoat applied via aqueous dispersion to overcome these limitations. Experimental results demonstrate that the composite coating significantly outperforms single-component modifications, improving stain resistance by 21.3% after 12 months of outdoor exposure. The surface remains brighter with markedly reduced pollutant accumulation. Mechanistically, SiO₂ serves as an inert mesoporous carrier that improves the dispersion and photostability of TiO₂, minimizing agglomeration and photocorrosion. Its inherent hardness and hydrophobicity reduce physical adsorption sites. Together, SiO₂ and TiO₂ create a nanoscale rough surface that enhances hydrophobicity through a lotus-like effect. Under UV irradiation, TiO₂ generates radicals that decompose organic pollutants and inhibit microbial growth, enabling efficient self-cleaning with rainwater. This synergistic mechanism addresses the limitations of individual nanoparticles, successfully integrating elasticity with long-term anti-fouling and durability. This composite demonstrates a significant advancement in stain resistance and overall durability, offering potential applications in energy-efficient and environmentally sustainable building technologies. Full article

This paper proposed an adaptive bandwidth Phase-Locked Loop (PLL) that integrates integer-N and fractional-N switching for energy-efficient RF synthesis in IoT and mobile applications. The architecture exploits wide-bandwidth integer-N mode for rapid lock acquisition, then seamlessly transitions to narrow-bandwidth fractional-N mode for high-resolution synthesis and noise optimization. The architecture features a bandwidth-reconfigurable loop filter with intelligent switching control that monitors phase error dynamics. A novel adaptive digital noise filter mitigates $\Delta \Sigma$ quantization noise, replacing conventional synchronous delay lines. The multi-loop structure incorporates a high-resolution digital phase detector to enhance frequency accuracy and minimize jitter across both operating modes. With 180 nm CMOS technology, the PLL consumes 13.2 mW, while achieving $-119$ dBc/Hz in-band phase noise and 1 $p{s}_{rms}$ integrated jitter. With an operating frequency range at 2.9–3.2 GHz from a 1.8 V supply, the circuit achieves a worst case fractional spur of −62.7 dBc, which corresponds to a figure of merit (FOM) of −228.8 dB. Lock time improvements of 70% are demonstrated compared to single-mode implementations, making it suitable for high-precision, low-power wireless communication systems requiring agile frequency synthesis. Full article

Large-scale integration of distributed energy resources (DERs) into distribution networks causes topological-operational situations with multidirectional power flows. One of the main components of distribution networks is the power transformer, which does not have the capabilities for real-time control of distribution network parameters with DERs. The use of solid-state transformers (SSTs) for connecting medium-voltage (MV) and low-voltage (LV) distribution networks of both alternating and direct current has great potential for constructing new distribution networks and enhancing the existing ones. Electricity losses in distribution networks can be reduced through the establishment of MV and LV DC networks. In hybrid AC-DC distribution networks, the SSTs can be especially effective, ensuring compensation for voltage dips, fluctuations, and interruptions; regulation of voltage, current, frequency, and power factor in LV networks; and reduction in the levels of harmonic current and voltage due to the presence of power electronic converters (PECs) and capacitors in the DC link. To control the operating parameters of hybrid distribution networks with solid-state transformers, it is crucial to develop and implement advanced control systems (CSs). The purpose of this review is a comprehensive analysis of the features of the creation of CSs SSTs when they are used in hybrid distribution networks with DERs to identify the most effective principles and methods for managing SSTs of different designs, which will accelerate the development and implementation of CSs. This review focuses on the design principles and control strategies for SSTs, guided by their architecture and intended functionality. The architecture of the solid-state transformer control system is presented with a detailed description of the main stages of control. In addition, the features of the SST CS operating under various topologies and operating conditions of distribution networks are examined. Full article

Digital twins (DTs) offer significant promise for condition-based maintenance of floating offshore wind turbines (FOWTs); however, existing solutions typically compromise either on physical rigor or real-time computational performance. This paper presents a real-time DT framework that resolves this trade-off by embedding a hydro-elastic reduced-order model (ROM) that accurately captures structural dynamics and fluid–structure interaction. Integrated in a cloud-ready Internet of Things architecture, the ROM reconstructs full-field displacements, von Mises stresses, and fatigue metrics with near real-time responsiveness. Validation on the 5 MW OC4-DeepCWind semi-submersible platform shows that the ROM reproduces finite-element (FEM) displacements and stresses with relative errors below 1%. A three-hour load case is solved in 0.69 min for displacements and 3.81 min for stresses on a consumer-grade NVIDIA RTX 4070 Ti GPU—over two orders of magnitude faster than the full FEM model—while one million fatigue stress histories (1000 hotspots × 1000 operating scenarios) are processed in 37 min. This efficiency enables continuous structural monitoring, rapid *what-if* assessments and timely decision-making for targeted inspections and adaptive control. By effectively combining physics-based reduced-order modeling with high-throughput computation, the proposed framework overcomes key barriers to DT deployment: computational overhead, physical fidelity and scalability. Although demonstrated on a steel platform, the approach is readily extensible to composite structures and multi-turbine arrays, providing a robust foundation for cost-effective and reliable deep-water wind-energy operations. Full article

Biomass-derived hard carbon (BHC) has attracted considerable attention as a sustainable and cost-effective anode material for sodium-ion batteries (SIBs), owing to its natural abundance, environmental friendliness, and promising electrochemical performance. This review provides a detailed overview of recent progress in the synthesis, structural design, and performance optimization of BHC materials. It encompasses key fabrication routes, such as high-temperature pyrolysis, hydrothermal pretreatment, chemical and physical activation, heteroatom doping, and templating techniques, that have been employed to control pore architecture, defect density, and interlayer spacing. Among these strategies, activation-assisted pyrolysis and heteroatom doping have shown the most significant improvements in sodium (Na) storage capacity and long-term cycling stability. The review further explores the correlations between microstructure and electrochemical behavior, outlines the main challenges limiting large-scale application, and proposes future research directions toward scalable production and integration of BHC anodes in practical SIB systems. Overall, these advancements highlight the strong potential of BHC as a next-generation anode for grid-level and renewable energy storage technologies. Full article

The increasing prevalence of common cold viruses and bacteria in daily life has heightened interest in sterilization lamp technologies. Compared with traditional mercury-based ultraviolet (UV) lamps, modern UV lamps offer advantages including extended operational lifespan, high energy efficiency, compact form factor, and the absence of hazardous materials, rendering them both safer and environmentally sustainable. In particular, UV-C LED lamps, which emit at short wavelengths, are capable of disrupting the molecular structure of DNA or RNA in microbial cells, thereby inhibiting cellular replication and achieving effective disinfection and sterilization. Conventional UV-C LED sterilization lamp driver circuits frequently employ a two-stage architecture, which requires a large number of components, occupies substantial physical space, and exhibits reduced efficiency due to multiple stages of power conversion. To address these limitations, this paper proposes a UV-C LED sterilization lamp driver circuit for an AC voltage supply, employing boundary conduction mode (BCM) control with integrated power factor correction (PFC). The proposed single-stage, single-switch topology combines a buck PFC converter and a flyback converter while recovering transformer leakage energy to further improve efficiency. Compared with conventional two-stage designs, the proposed circuit reduces the number of power switches and components, thereby lowering manufacturing cost and enhancing overall energy conversion efficiency. The operating principles of the proposed driver circuit are analyzed, and a prototype is developed for a 110 V AC input with an output specification of 10.8 W (90 V/0.12 A). Experimental results demonstrate that the prototype achieves an efficiency exceeding 92%, a power factor of 0.91, an output voltage ripple of 1.298%, and an output current ripple of 4.44%. Full article

Cryogenic propellant sloshing presents significant challenges in aerospace systems, inducing vehicle instability, structural fatigue, energy losses, and complex thermal management issues. This review synthesizes experimental, analytical, and numerical advances with an emphasis on energy dissipation and conversion efficiency in propellant storage and transfer. Recent developments in computational fluid dynamics (CFD) and AI-driven digital-twin frameworks are critically examined alongside the influences of tank materials, baffle configurations, and operating conditions. Unlike conventional fluids, cryogenic propellants in microgravity and within composite overwrapped pressure vessels (COPVs) exhibit unique thermodynamic and dynamic couplings that remain only partially characterized. Prior reviews have typically treated these factors in isolation; here, they are unified through an integrated perspective linking cryogenic thermo-physics, reduced-gravity hydrodynamics, and fluid–structure interactions. Persistent research limitations are identified in the areas of data availability, model validation, and thermo-mechanical coupling fidelity, underscoring the need for scalable multi-physics approaches. This review’s contribution lies in consolidating these interdisciplinary domains while outlining a roadmap toward experimentally validated, AI-augmented digital-twin architectures for improved energy efficiency, reliability, and propellant stability in next-generation aerospace missions. Full article

Battery Electric Vehicles (BEVs) technology is rapidly emerging as the cornerstone of sustainable transportation, driven by advancements in battery technology, power electronics, and modern drivetrains. This paper presents a comprehensive review of current and next-generation BEV powertrain architectures, focusing on five key subsystems: battery energy storage system, electric propulsion motors, energy management systems, power electronic converters, and charging infrastructure. The review traces the evolution of battery technology from conventional lithium-ion to solid-state chemistries and highlights the critical role of battery management systems in ensuring optimal state of charge, health, and safety. Recent innovations by leading automakers are examined, showcasing advancements in cell formats, motor designs, and thermal management for enhanced range and performance. The role of power electronics and the integration of AI-driven strategies for vehicle control and vehicle-to-grid (V2G) are analyzed. Finally, the paper identifies ongoing research gaps in system integration, standardization, and advanced BMS solutions. This review provides a comprehensive roadmap for innovation, aiming to guide researchers and industry stakeholders in accelerating the adoption and sustainable advancement of BEV technologies. Full article

In this study, the energy performance of traditional, modern, and insulated wall assemblies in a heritage residential building in Al Salt city, Jordan, is evaluated using the simulation software DesignBuilder version 7.0.2.004. The case study compares the thermal behavior of traditional thick limestone walls, modern reinforced concrete and block-based walls, and contemporary insulated systems under local climatic conditions. The results show that traditional stone walls exhibit limited energy efficiency and require insulation to meet contemporary standards. However, they perform better than modern concrete walls based on their thermal mass. While concrete walls with inadequate insulation exhibit the poorest performance and are associated with significantly higher energy demand and CO₂ emissions, insulated wall systems that combine stone with insulation layers demonstrate the best thermal performance and achieve substantial reductions in energy use and environmental impact. These findings emphasize the feasibility of upgrading heritage buildings through the integration of modern insulated wall assemblies, which can lead to considerable energy savings and a lowered carbon footprint while simultaneously keeping the architectural identity and cultural value. Full article

Unmanned aerial vehicles (UAVs) are redefining both civilian and defense operations, with swarm-based architectures unlocking unprecedented scalability and autonomy. However, these advancements introduce critical security challenges, particularly in location verification and authentication. This review provides a comprehensive synthesis of hardware security primitives (HSPs)—including Physical Unclonable Functions (PUFs), Trusted Platform Modules (TPMs), and blockchain-integrated frameworks—as foundational enablers of trust in UAV ecosystems. We systematically analyze communication architectures, cybersecurity vulnerabilities, and deployment constraints, followed by a comparative evaluation of HSP-based techniques in terms of energy efficiency, scalability, and operational resilience. The review further identifies unresolved research gaps and highlights transformative trends such as AI-augmented environmental PUFs, post-quantum secure primitives, and RISC-V-based secure control systems. By bridging current limitations with emerging innovations, this work underscores the pivotal role of hardware-rooted security in shaping the next generation of autonomous aerial networks. Full article