Search Results (16,987)

The absence of overhead catenary systems in contactless trams imposes stringent requirements on onboard energy efficiency and real-time power management. Hybrid energy storage systems combining batteries and supercapacitors provide an effective solution; however, conventional energy management strategies often suffer from limited global optimality under frequent traction–braking conditions. To address this issue, this paper proposes a variable-horizon model predictive control (MPC)-based energy management strategy for a battery–supercapacitor hybrid power supply system in contactless trams. A power-level-matching method is first adopted for capacity configuration, and the MPC prediction horizon is then dynamically adjusted to cover the entire traction phase, enabling global energy loss optimization while satisfying voltage, current, and SOC constraints. Simulation results obtained in MATLAB/Simulink demonstrate that the proposed strategy effectively suppresses excessive battery current and premature supercapacitor depletion. Compared with the conventional single-step MPC, the total energy loss is reduced by 9.88%, indicating improved energy efficiency and operational performance. Full article

This paper proposes an improved state-of-charge (SOC)-based adaptive droop control strategy for photovoltaic DC microgrids with distributed energy storage units (DESUs). To overcome the slow SOC equalization and limited adaptability of conventional droop control methods, a nonlinear arctangent-based droop coefficient adjustment mechanism is introduced to enhance regulation sensitivity under small SOC deviations. In addition, a capacity compensation factor and an acceleration term are incorporated to improve proportional power sharing and SOC convergence speed among heterogeneous storage units. To further evaluate the engineering significance of SOC balancing performance, a time-integrated SOC deviation index is introduced to analyze the cumulative imbalance effect on battery degradation and lifecycle operation. By reducing the SOC imbalance duration, the proposed strategy contributes to mitigating uneven battery aging and may potentially reduce long-term battery replacement costs. Simulation results under discharging, charging, and irradiance-variation scenarios demonstrate that the proposed strategy significantly improves SOC-balancing performance compared with conventional SOC-based droop control. Across the three operating modes, the average SOC balancing time has been reduced by 52.6%. The proposed method provides an effective and economically sustainable control framework for distributed energy storage coordination in DC microgrids. Full article

Radiotherapy is a cornerstone of breast cancer treatment, but its efficacy is frequently limited by intrinsic and acquired radioresistance as well as dose-limiting toxicity to surrounding normal tissues. Nanoparticle-mediated radiosensitization has emerged as a promising strategy to enhance the therapeutic index of irradiation by combining physical dose amplification with biological, microenvironmental, and immunological modulation. In this systematic review, we evaluated preclinical evidence on nanoparticle-mediated radiosensitization in breast cancer, with emphasis on nanoplatform design, mechanistic patterns, therapeutic efficacy, and translational relevance. A total of 66 studies published between 2015 and 2026 were included. The identified systems encompassed a broad range of materials, including gold-, silver-, platinum-, bismuth-, gadolinium-, polymer-, lipid-, and hybrid-based nanoplatforms, frequently incorporating targeting ligands, catalytic components, biomimetic coatings, or therapeutic payloads. Enhanced radiation responses were most commonly associated with high-atomic-number (high-Z)-mediated energy deposition, increased reactive oxygen species generation, and enhanced DNA damage persistence. Additional mechanisms, including redox modulation, hypoxia targeting, regulated cell death, and immune activation, reflect the evolution of nanoparticle-assisted radiotherapy from predominantly physical radioenhancement toward multifunctional physicobiological strategies. Triple-negative breast cancer models predominated throughout the literature. Across preclinical models, nanoparticle-assisted irradiation consistently improved clonogenic survival, tumor control, and, in selected studies, survival. However, substantial heterogeneity in study design and limited use of rigorous radiobiological endpoints restricted cross-study comparability. The available preclinical evidence indicates that the most promising nanoparticle-mediated radiosensitization strategies integrate physical dose enhancement with biologically active mechanisms targeting oxidative stress, hypoxia, persistent DNA damage, immune signaling, and tumor microenvironmental resistance. Collectively, these findings suggest that the field is evolving from predominantly physical radioenhancement toward multifunctional, mechanism-driven physicobiological strategies. However, clinical translation remains constrained by methodological heterogeneity and limited radiobiological validation, highlighting the need for standardized preclinical evaluation and clinically feasible nanoplatforms tailored to subtype-specific mechanisms of radioresistance. Full article

Cyber-physical power systems (CPPSs) are a crucial component of smart grids, integrating physical power systems with advanced information and communication technologies to achieve efficient, reliable, and intelligent energy management and control. However, with the widespread deployment of information technology, CPPSs face increasingly severe security threats and privacy protection challenges, such as data leakage, identity forgery, and impersonation, which can compromise the secure and stable operation of CPPSs. To counter these threats and protect privacy, cryptographic technique is developed to provide fundamental and powerful tools, supporting secure authentication, data integrity checking, privacy preservation, and trusted communication between connected devices in CPPSs. We systematically review the research progress on security authentication and privacy protection in CPPSs from a cryptographic perspective. Our survey analyzes the major security threats faced by CPPSs, along with the impact of various attacks on system data. We explore mainstream cryptographic algorithms, including digital signatures, key agreement protocols, signcryption authentication, homomorphic encryption, and blockchain-based security mechanisms that are capable of resisting cyber attacks and ensuring reliable decision-making and control in CPPSs. This work also provides the trends and challenges regarding the intersection of cryptography and networked control, blockchain scalability, and convergence of cryptography and artificial intelligence in CPPSs. Full article

The rapid adoption of electric vehicles (EVs) has intensified the demand for advanced energy storage technologies capable of delivering high energy density, high power density, enhanced safety, and extended service life. Although lithium-ion batteries remain the dominant energy storage technology for EVs, their limited power capability, thermal degradation, and accelerated aging under high transient loads constrain vehicle performance. Battery–supercapacitor hybrid energy storage systems (HESSs) have emerged as a promising solution by combining the high energy density of batteries with the high-power density and rapid charge–discharge capability of supercapacitors. However, the increasing complexity of HESS architecture requires intelligent energy management strategies to optimize power allocation, battery protection, thermal regulation, and overall system efficiency. Existing review papers primarily address individual aspects of HESS architecture, battery management, or artificial intelligence (AI)-based control, leaving a lack of a unified review integrating these topics. This paper addresses this gap by reviewing 181 publications published between 2020 and 2026, covering HESS architectures, conventional and AI-driven energy management strategies, machine learning, deep learning, reinforcement learning, battery state estimation, diagnostics, prognostics, thermal management, and fault diagnosis. The reviewed studies are critically analyzed to assess the impact of AI on battery lifetime, regenerative braking, charging performance, thermal behavior, and energy efficiency. The review further identifies emerging research directions, including explainable AI, digital twins, federated learning, edge intelligence, vehicle-to-grid integration, and cybersecurity-aware energy management. The findings indicate that AI-based approaches generally demonstrate greater adaptability, predictive capability, and battery protection than conventional methods under dynamic operating conditions, although challenges related to computational complexity, real-time implementation, data availability, explainability, cybersecurity, and standardization remain significant barriers to large-scale deployment. Full article

Supplying shore-side electricity to ships at berth, a practice known as cold ironing, removes the emissions of their auxiliary engines, yet the resulting electricity demand is large, highly seasonal and hard to serve economically from the grid at the small and medium-sized ports that make up most of the European network. This study asks how to meet that demand affordably and cleanly. It develops a smart-sizing and energy-management framework for a grid-connected hybrid renewable energy system that jointly optimizes solar photovoltaic and wind capacity together with a combined battery-and-hydrogen storage envelope. An energy-conserving stochastic reconstruction of the hourly cold-ironing demand is embedded within a genetic algorithm that minimizes the levelized cost of energy and the carbon footprint, and the system is operated by a transparent, priority-based controller. On a full year of real operational data from a Mediterranean port, the optimizer selects 380 kilowatts of photovoltaic capacity and a 2064 kilowatt-hour, battery-dominated storage envelope, reaching a renewable penetration equal to 76 percent of annual demand, with 57 percent of demand met without the grid. Relative to grid-only cold ironing it lowers the levelized cost of energy by about 10 percent on a screening basis, before life-cycle costs bring it to roughly grid parity, while cutting greenhouse-gas emissions by 45 percent; emissions fall 72 percent relative to auxiliary engines. Storage capacity, not oversized renewable generation, proves decisive for deep decarbonization, and battery storage dominates the cost-optimal design for this diurnal load. The framework gives port operators a transferable, data-driven decision-support tool. Full article

Biochar has attracted increasing attention for aquatic pollution control, particularly due to its capacity to accelerate the rate-limiting steps of denitrification in wastewater treatment. While early research primarily focused on the adsorption capacity of biochar, recent studies have increasingly investigated its role as a redox-active mediator that facilitates electron transfer. This review critically synthesizes the multifaceted mechanisms of biochar-enhanced denitrification, establishing a link between synthesis parameters (feedstock, pyrolysis kinetics) and physicochemical functionalities (pore architecture, redox-active functional groups). Specifically, we elucidate how precise regulation of pyrolysis temperature dictates the dominant electron transfer pathway: low-temperature biochar (<500 °C) facilitates electron shuttling via oxygen-containing functional groups (e.g., quinone moieties), whereas high-temperature biochar (>700 °C) promotes direct interspecies electron transfer (DIET) through graphitic conduction. We systematically decouple biochar-mediated electron transfer into three pathways: functional group-driven shuttling, solid-state conductive matrix transfer via conjugated π-electrons, and material-assisted DIET. Crucially, we emphasize that validating true DIET requires direct biological evidence of electroactive machinery. Furthermore, the review details how biochar modulates the biological microenvironment, upregulating key denitrification genes (narG, nirS/K, nosZ) and enriching functional microbial consortia. By integrating advances in surface modification—such as heteroatom doping and metal loading—we propose strategies to engineer biochar for optimized nitrate-to-nitrogen conversion. Future perspectives underscore the need for balancing electron-donating capacity with structural stability, developing low-energy functionalization techniques, and conducting life-cycle assessments to facilitate the scale-up of sustainable, high-efficiency nitrogen removal systems. Full article

Interfacial bond failure is a common form of distress in rigid–flexible composite pavements, especially in tunnel environments with harsh service conditions. Epoxy-emulsified asphalt (EEA) is widely used as a high-performance interlayer bond coat, but its dynamic damage evolution under coupled thermomechanical loading remains insufficiently characterised. In this work, 45° static oblique shear tests and stress-controlled dynamic shear fatigue tests were performed on a C40 concrete-EEA-asphalt mixture composite system. Tests covered a temperature range of −10 °C to 45 °C, loading frequencies of 1 to 15 Hz, and three stress levels (0.3, 0.4, 0.5). An optimised geometric tangent method (GTM) was adopted to objectively locate the fatigue failure inflexion point, reducing the empirical bias inherent in traditional stiffness degradation analysis. Test results showed that an EEA application rate of 0.8 kg/m² yielded the best overall interface performance, balancing mechanical interlocking and cohesive strength. At this application rate, the interfacial peak shear strength reached 1.72 MPa, with improved interfacial deformation compatibility and energy dissipation capacity. Fatigue damage followed a distinct three-stage stiffness degradation pattern. High temperatures and low loading frequencies accelerated rheological behaviour of the asphalt phase, shortened the stable damage propagation phase, and promoted premature interlayer slippage. Based on the experimental data, a phenomenological fatigue life prediction model was established, incorporating temperature, loading frequency and stress level. The model supports quantitative assessment of progressive interfacial damage and provides practical reference for structural durability design and life-cycle maintenance of composite tunnel pavements. Full article

Electric vehicles equipped with in-wheel motors provide packaging, controllability, and drivetrain-simplification advantages; however, the increase in wheel-side unsprung mass can intensify vibration transmission to the chassis, seat, and occupant. This paper presents a coordinated active seat and active suspension control strategy for an integrated 8-DOF quarter-car model that includes an in-wheel motor, an active seat suspension, and a 4-DOF seated driver body model. The proposed controller combines a Harmony Search (HS)-optimized proportional–integral–derivative (PID) feedback baseline with a repeatable-disturbance feedforward compensation term. The HS-PID loop provides baseline transient attenuation, while the feedforward term compensates the repeatable component of the bump-induced disturbance transmitted through the coupled seat–vehicle system. The controller is evaluated against passive suspension, active-seat-only control, active-vehicle-suspension-only control, and an HS-PID baseline under repeated bump/shock excitation. The results show that coordinated actuation reduces occupant displacement and acceleration responses relative to the benchmark cases. The discussion explains the active-seat-only peak-acceleration amplification, the different magnitudes of displacement and acceleration improvements, and the practical implications of suspension stroke and actuator-force limits. The reported conclusions are therefore confined to the repeated bump/shock condition considered in this numerical study; broader ride-comfort generalization requires standardized whole-body vibration metrics, random-road validation, speed variation, parametric uncertainty analysis, and drivetrain energy evaluation. Full article

This paper presents a comprehensive review of control techniques, simulation mechanisms, and validation methods applied to DC-DC converters, with a focus on high-step-up topologies used in renewable energy systems such as photovoltaic and wind power applications. Control strategies including classical PID, fuzzy logic, sliding mode, and model predictive control (MPC) are analyzed in terms of performance, robustness, and implementation complexity. Simulation platforms and hardware-in-the-loop (HIL) validation frameworks are also discussed as key enablers for rapid prototyping. The findings reveal a clear trend toward intelligent and hybrid control schemes that combine nonlinear techniques with artificial intelligence to address the inherent nonlinearities and parametric uncertainties of DC-DC converters. However, challenges remain in real-time implementation due to computational demands, which drives the need for future developments focused on the (i) integration of AI-based controllers with low-cost embedded platforms, (ii) standardization of HIL-based validation workflows, and (iii) optimization of converter topologies for specific applications such as electric vehicle charging and photovoltaic grid integration. Looking forward, the convergence of advanced control algorithms, real-time validation platforms, and application-specific converter design is expected to define the next generation of power electronics systems, enabling more efficient, reliable, and scalable renewable energy integration. Full article

Drilling fluids are essential in oil and gas operations for wellbore stability, cuttings transport, pressure control, and fluid-loss reduction. Water-based drilling fluids (WBDFs) are widely used because of their cost-effectiveness and lower environmental impact compared with oil-based systems; however, they often suffer from fluid loss into the formation and lower rheological performance. This laboratory-scale study investigates the feasibility of using rice and bread waste powders as bio-based additives for WBDFs to mitigate fluid loss. The collected food wastes were dried, milled, and sieved into three particle sizes of fine (150 µm), very fine (75 µm), and ultrafine (45 µm). The prepared powders were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX). A total of 18 drilling-fluid formulations were prepared using rice and bread powders at concentrations of 1 wt%, 2 wt%, and 3 wt%. Filtration tests were conducted under low-pressure low-temperature (LPLT) conditions of 100 psi and 25 °C and high-pressure high-temperature (HPHT) conditions of 1500 psi and 70 °C, while rheological properties were measured using a rotational viscometer. The results showed that additive type, particle size, and concentration strongly influenced WBDF performance. The best-performing formulation was WBDF with added rice powder at 45 µm and 3 wt% (RC45-3), which reduced fluid loss from 19.5 mL to 6.1 mL, corresponding to a reduction of approximately 68.7% at LPLT. Under HPHT conditions, the same formulation reduced fluid loss from 36.5 mL to 11.4 mL, corresponding to a reduction of approximately 68.8%. RC45-3 also produced the thinnest measured filter cake, reducing filter-cake thickness from 5.0 mm for the base mud to 0.52 mm. The formulation maintained shear-thinning behavior and produced suitable gel strength values, indicating improved suspension capacity. The improved performance of rice powder is attributed to its fine particle size, favorable morphology, and ability to form a compact, low-permeability filter cake. Overall, the findings indicate that processed rice waste powder has potential as a low-cost, bio-based fluid-loss-control agent for WBDFs, although further testing in field-representative mud systems is required before practical application. Full article

Ammonia is increasingly regarded as a carbon-free energy carrier for hard-to-electrify power sectors, including marine propulsion, heavy-duty transport, and distributed generation. Its direct use in internal combustion engines, however, is constrained by high ignition energy, low laminar flame speed, narrow flammability limits, slow low-temperature chemistry, and strong trade-offs among efficiency, nitrogen-containing emissions, and unburned ammonia slip. Hydrogen enrichment is one of the most effective routes for improving ammonia combustion reactivity, but it also introduces a multivariable control problem: hydrogen fraction, ammonia injection timing, injection mode, air-path dilution, ignition strategy, and aftertreatment operation are tightly coupled and strongly condition-dependent. This review synthesizes recent progress in ammonia–hydrogen and ammonia-based dual-fuel engine control from a control-oriented perspective. The discussion first summarizes application scenarios, nonlinear combustion-mode transitions, emission-formation pathways, and control-relevant metrics. It then compares actuator-level strategies, including ammonia injection timing and staging, port and direct injection, hydrogen energy-fraction scheduling, excess-air-ratio and EGR control, high-energy ignition, and turbulent jet ignition. Advanced optimization methods are further reviewed, with emphasis on model predictive control, control-oriented combustion and emission models, artificial-intelligence-based virtual sensors, and reinforcement-learning control. The analysis shows that the central challenge is no longer whether ammonia can burn in an engine, but how a controller can keep the system inside a narrow moving window bounded by misfire, knock, NO_x, N₂O, and NH₃ slip. Finally, future research priorities are proposed, including engine–aftertreatment co-optimization, physics-informed virtual sensing, digital-twin-assisted calibration, lightweight deployment on electronic control units, and robust control under fuel and aging uncertainty. Full article

The increasing pressure on water resources is one of the most critical challenges of the 21st century. Demographic, industrial, and climatic factors are drastically reducing the availability of fresh water, with particularly pronounced effects in arid regions and the Mediterranean basin. Agriculture, which accounts for about 70% of global water withdrawals, is at the centre of this crisis, making it essential to explore unconventional sources such as brackish water. Desalination emerges as a key technology to address this challenge. Electrodialysis offers an attractive alternative, particularly suitable for moderately salty water (1000–5000 mg/L of total dissolved solids), thanks to its energy efficiency within specific salinity ranges and the ability to precisely control the quality of the produced water. At the same time, agrivoltaic systems that integrate energy production and agriculture are spreading, requiring compact, modular treatment devices that can be integrated with renewable sources. This research objective is the design and building of an affordable and reproducible electrodialysis (ED) prototype, equipping the system with automated sensor-based control, validating the device performance on brackish water and analyzing the feasibility of integration in agrivoltaic contexts. Full article

One of the most important factors affecting broiler production efficiency is providing appropriate indoor microclimatic conditions, which are significantly influenced by the heating system used. This study presents the results of long-term experimental investigations conducted in two buildings equipped with different heating systems. One of the buildings was equipped with a wall heating system supported by air heaters, while the other was equipped with an underfloor heating system During the winter production cycle, the indoor air temperature in the initial period ranged from 27.2 to 33.2 °C with the underfloor heating system and from 31.9 to 40.0 °C with the conventional radiator-based system. Even greater differences were observed in floor surface temperature, which ranged from 28.0 to 31.4 °C and from 11.0 to 22.0 °C, respectively. In the building with the underfloor heating system, the relative air humidity fluctuated from 43.1% to 66.8%, while in the building without an underfloor heating system, it ranged from 20.3% to 58.6%. During the first week of the winter production cycle, the use of underfloor heating reduced broiler mortality by 77.3%. These findings provide a basis for further research on heat and moisture transfer processes and can support the development and modernization of energy-efficient heating systems in livestock buildings. The results contribute to current efforts toward the sustainable development of poultry production by improving environmental control and enhancing energy efficiency. Full article

The issue of thermal runaway in power batteries of new-energy vehicles occurs frequently, posing a serious threat to life and property safety. This study aims to develop a high-performance fire-proof coating to address this problem. Specifically, the research focused on constructing an organic-inorganic composite intumescent fire-resistant coating, with modified halloysites (Ti-HNTs) serving as the key component. In this coating system, the intumescent flame-retardant (IFR) system and Ti-HNTs were employed as the organic and inorganic components, respectively, while water-based epoxy resin emulsion was selected as the matrix material. Through the utilization of XPS, FTIR, and SEM techniques, it was verified that the Ti-HNTs were successfully modified and integrated well with the coating matrix. Following further optimization of the Ti-HNTs proportion and coating thickness, it was determined that the coating containing 4% Ti-HNTs with a designed thickness of 1.5 mm exhibited the optimal fire-proofing performance. In the fire-resistance experiment, after 10 min of testing, the temperature of this coating could reach a minimum of 215.9 °C. Compared to the control group, its heat-insulation effect was enhanced by 49.4%, with an expansion multiplier of 37.7 and a maximum smoke density of 22.55. These results were significantly superior to those of the control group without the addition of Ti-HNTs. SEM analysis indicated that the coating could form a uniform and dense carbon layer, with an inner surface featuring a honeycomb-bubble structure. This SEM-analyzed Ti-HNTs-modified fire-proof coating demonstrated excellent fire resistance and thermal-isolation effects in new-energy vehicle batteries, thus providing reliable fire protection for the batteries. Additionally, impact-resistance tests revealed that the coating could withstand a simulated battery pressure-relief impact without penetration, maintaining its structural integrity and thermal-barrier function. This further validated its reliability for battery fire protection. Full article