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Electric vehicles (EVs) have gained significant popularity globally during the past decade. This is mostly due to their reduced emissions of hydrocarbons and greenhouse gases. Electric vehicles acquire their electricity via wireless energy transmission, thereby circumventing the challenges associated with conventional techniques. The coils that transmit and receive signals deteriorate in performance and age as temperatures increase. Under extreme conditions, this may result in fire hazards and further safety issues. This article examined the electromagnetic and thermal dispersion of a magnetically coupled coil model for electric vehicles. This paper studied the electromagnetic and temperature distribution of the magnetically coupled coil model for electric vehicles. The coils were designed utilizing ANSYS software, with boundary conditions and pertinent parameters configured accordingly. The transmitter and receiver coils were identical in dimensions, with an inner diameter of 100 mm, an outer diameter of 295 mm, and an air gap of 60 mm between them. The magnetic coil was simulated and analyzed using copper as a material. In the aligned positions, the coupling coefficient between the transmitter and receiver coil was 0.168, its maximum temperature was 16.92 °C, and it was lower for the safety of the human body. An actual prototype was built to confirm the simulation results and to establish that the methodology employed in this research is applicable to the design of magnetic coils for a wireless charging system for electric vehicle models. Full article

Decarbonizing heavy-duty freight transport is essential for achieving climate neutrality targets. Although internal combustion engine (ICE) trucks currently dominate logistics, they contribute substantially to greenhouse gas emissions. Zero-emission alternatives, such as battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (H2), provide different decarbonization pathways; however, their relative roles remain contested, particularly in small economies. While BEVs benefit from technological maturity and declining costs, hydrogen offers advantages for high-payload, long-haul operations, especially within energy-intensive cold supply chains. The aim of this paper is to examine the gradual transition from ICE trucks to hydrogen-powered vehicles with a specific focus on cold-chain logistics, where reliability and energy intensity are critical. The hypothesis is that applying a system dynamics forecasting approach, incorporating investment costs, infrastructure coverage, government support, and technological progress, can more effectively guide transition planning than traditional linear methods. To address this, the study develops a system dynamics economic model tailored to the structural characteristics of a small economy, using a European case context. Small markets face distinct constraints: limited fleet sizes reduce economies of scale, infrastructure deployment is disproportionately costly, and fiscal capacity to support subsidies is restricted. These conditions increase the risk of technology lock-in and emphasize the need for coordinated, adaptive policy design. The model integrates acquisition and maintenance costs, fuel consumption, infrastructure rollout, subsidy schemes, industrial hydrogen demand, and technology learning rates. It incorporates subsystems for fleet renewal, hydrogen refueling network expansion, operating costs, industrial demand linkages, and attractiveness functions weighted by operator decision preferences. Reinforcing and balancing feedback loops capture the dynamic interactions between fleet adoption and infrastructure availability. Inputs combine fixed baseline parameters with variable policy levers such as subsidies, elasticity values, and hydrogen cost reduction rates. Results indicate that BEVs are structurally more favorable in small economies due to lower entry costs and simpler infrastructure requirements. Hydrogen adoption becomes viable only under scenarios with strong, sustained subsidies, accelerated station deployment, and sufficient cross-sectoral demand. Under favorable conditions, hydrogen can approach cost and attractiveness parity with BEVs. Overall, market forces alone are insufficient to ensure a balanced zero-emission transition in small markets; proactive and continuous government intervention is required for hydrogen to complement rather than remain secondary to BEV uptake. The novelty of this study lies in the development of a system dynamics model specifically designed for small-economy conditions, integrating industrial hydrogen demand, policy elasticity, and infrastructure coverage limitations, factors largely absent from the existing literature. Unlike models focused on large markets or single-sector applications, this approach captures cross-sector synergies, small-scale cost dynamics, and subsidy-driven points, offering a more realistic framework for hydrogen truck deployment in small-country environments. The model highlights key leverage points for policymakers and provides a transferable tool for guiding freight decarbonization strategies in comparable small-market contexts. Full article

Renewable Energy Communities (RECs) are a cornerstone of the European Union’s energy transition strategy, promoting decentralized and participatory energy models. A fundamental design aspect of RECs is the choice of Keys of Repartition (KoRs), which govern the allocation of locally generated energy among participants. This study evaluated the economic and technical impacts of four KoR strategies—static, dynamic (based on load or production), and hybrid—within the Portuguese regulatory framework. A simulation-based methodology was employed, considering both small and large-scale communities, with and without energy storage systems, including stationary batteries and electric vehicles (EVs). Results show that storage integration markedly improves self-sufficiency and self-consumption, with stationary batteries playing the most significant role, while EVs provided only a residual contribution. Furthermore, the results demonstrated that the choice of KoR has a decisive impact on REC performance: in small-scale communities, outcomes depend strongly on participant demand profiles and storage availability, whereas in large-scale communities, operational rules become the key factor in ensuring efficient energy sharing, higher self-consumption, and improved balance between generation and demand. Full article

Power converters are essential for solar energy systems but achieving over 96% efficiency at 1 kW and 300 kHz with compact magnetic and EMC compliance remains challenging for high-power-density PV applications. This study presents the design, modeling, and experimental validation of a 1 kW two-phase interleaved boost converter operating from 12 V input to 48 V/20 A output, featuring a single EE32 Litz-wound coupled-core inductor with coupling coefficient k = −0.475 that reduces per-phase current ripple to just 120 mA (0.6% relative) at full load, a load-selective active zero-current switching (ZCS) circuit activated above 5 A threshold via DCR sensing to minimize switching losses without light-load penalties, and digital peak-current control with 2P2Z compensator implemented on an XMC4200 microcontroller, ensuring robust stability. Experimental results demonstrate peak efficiency of 98.6% at approximately 190 W load, full-load efficiency of approximately 96% with total losses limited to 40 W dominated by conduction rather than switching, thermal rise below 80 °C on key components, voltage regulation with less than 1% deviation down to 2 A minimum load, and full compliance with electromagnetic compatibility standards, including EN 55014-1/2 and EN 61000-4-2 ESD testing. The novel integration of selective ZCS, single-core magnetic, and high-frequency operation outperforms prior interleaved boost converters, which typically achieve 94–97% peak efficiency at lower switching frequencies of 20–100 kHz using multiple inductors or complex always-active resonant networks, making this solution particularly suitable for compact photovoltaic micro-converters, electric vehicles, and industrial power supplies requiring high efficiency, reliability, and regulatory compliance. Full article

Despite growing interest in positive-energy and net-zero-energy buildings (NZEBs), few studies have addressed the integration of biobased construction with building-integrated photovoltaics (BIPV) under hot–dry climate conditions, particularly in Morocco and North Africa. This study fills this gap by presenting a simulation-based evaluation of energy performance and renewable energy integration strategies for a residential building in the Fes-Meknes region. Two structural configurations were compared using dynamic energy simulations in DesignBuilder/EnergyPlus, that is, a conventional concrete brick model and an eco-constructed alternative based on biobased wooden materials. Thus, the wooden construction reduced annual energy consumption by 33.3% and operational CO₂ emissions by 50% due to enhanced thermal insulation and moisture-regulating properties. Then multiple configurations of the solar energy systems were analysed, and an optimal hybrid off-grid hybrid system combining rooftop photovoltaic, BIPV, and lithium-ion battery storage achieved a 100% renewable energy fraction with an annual output of 12,390 kWh. While the system incurs a higher net present cost of $45,708 USD, it ensures full grid independence, lowers the electricity cost to $0.70/kWh, and improves occupant comfort. The novelty of this work lies in its integrated approach, which combines biobased construction, lifecycle-informed energy modelling, and HOMER-optimised PV/BIPV systems tailored to a hot, dry climate. The study provides a replicable framework for designing NZEBs in Morocco and similar arid regions, supporting the low-carbon transition and informing policy, planning, and sustainable construction strategies. Full article

This study employs molecular dynamics simulations to investigate the frictional behavior of fullerene nano-additives on Fe-C alloy surfaces under varying loads and temperatures, focusing on boundary lubrication conditions. The results show that the x-direction friction force exhibits minimal sensitivity to normal pressure due to the high rigidity of fullerene molecules, which limits variations in real contact area and atomic interactions. In contrast, temperature has a significant effect: as it rises, enhanced atomic vibrations and thermal activation lower energy barriers for sliding. The coefficient of friction (COF) consistently decreases with both increasing load and temperature, driven by the mechanism of thermally activated motion. Although partial rotational motion from sliding to rolling friction was not explicitly observed in the simulations, the study remains within the sliding-dominated regime, highlighting the importance of temperature over load in controlling friction. A linear relationship between $\ln COF$ and $1/k_{B}T$ yields an average activation energy of ~0.03 eV, supporting a thermally activated friction mechanism. By introducing a composite parameter that combines load and temperature effects, the study provides a predictive framework for modeling friction behavior under thermo-mechanical coupling. These findings enhance the understanding of the friction-reducing capabilities of fullerene additives and offer a foundation for designing advanced nano-lubricants in boundary lubrication systems. Full article

Low-viscosity epoxy-containing diluents are used to reduce the initial viscosity of highly filled, wear-resistant epoxy systems and to improve filler wetting and dispersion. This study determined physical parameters by an atomic-increment approach and electronic descriptors using the Parametric Method 3 (PM3) semi-empirical method. Clear relationships were established between the effective molar cohesion energy and the solubility parameter with van der Waals volume. Linear dependencies were also obtained between the diluent surface tension and spreading coefficients on model high-hardness fillers, including silicon carbide, boron carbide, and normal corundum. The activity of epoxy diluents depends on the lowest unoccupied molecular orbital energy. These diluents influence processing and the final physical and mechanical properties of composites, making their selection critical for strength, hardness, and wear resistance. Computational analysis enables prediction of diluent behavior, reducing experimental time and cost. Integrating physical and quantum-chemical data into epoxy diluent design accelerates the search for optimal components and improves production of durable, high-performance epoxy composites. Full article

This study proposes an artificial intelligence (AI)-powered multimodal system designed to enhance the appreciation of traditional poetry, using Japanese haiku as the primary application domain. At the core of the system is an intelligent data analysis pipeline that extracts key emotional features from poetic texts. A fine-tuned Japanese BERT model is employed to compute three affective indices—valence, energy, and dynamism—which form a quantitative emotional representation of each haiku. These features guide a generative AI workflow: ChatGPT constructs structured image prompts based on the extracted affective cues and contextual information, and these prompts are used by DALL·E to synthesize stylistically consistent watercolor illustrations. Simultaneously, background music is automatically selected from an open-source collection by matching each poem’s affective vector with that of instrumental tracks, producing a coherent multimodal (text, image, sound) experience. A series of validation experiments demonstrated the reliability and stability of the extracted emotional features, as well as their effectiveness in supporting consistent cross-modal alignment. These results indicate that poetic emotion can be represented within a low-dimensional affective space and used as a bridge across linguistic and artistic modalities. The proposed framework illustrates a novel integration of affective computing and natural language processing (NLP) within cultural computing. Because the underlying emotional representation is linguistically agnostic, the system holds strong potential for cross-cultural extensions, including applications to Chinese classical poetry and other forms of traditional literature. Full article

This paper presents an energy-aware Artificial Intelligence of Things framework designed for intelligent remote device control in residential settings. The system architecture is grounded in the Power Administration Device (PAD), a cost-effective and non-intrusive smart plug prototype that measures real-time electricity consumption and actuates appliance power states. The PAD transmits data to a scalable, cross-platform cloud infrastructure, which powers a web-based interface for monitoring, configuration, and multi-device control. Central to this framework is Cross-Feature Time-MoE, a novel neural forecasting model that processes the ingested data to predict consumption patterns. Integrating a Transformer Decoder with a Top-K Mixture-of-Experts (MoE) layer for temporal reasoning and a Bilinear Interaction Layer for capturing complex cross-time and cross-feature dependencies, the model generates accurate multi-horizon energy forecasts. These predictions drive actionable recommendations for device shut-off times, facilitating automated energy efficiency. Simulation results indicate that this system yields substantial reductions in energy consumption, particularly for high-wattage appliances, providing a user-friendly, scalable solution for household cost savings and environmental sustainability. Full article

The increasing adoption of lithium-ion (Li-ion) batteries in electric vehicles (EVs) and renewable energy systems has heightened the demand for efficient Battery Thermal Management Systems (BTMS). Effective thermal regulation is critical to prevent performance degradation, extend battery lifespan, and mitigate safety risks such as thermal runaway. Liquid cooling has become the dominant strategy in commercial EVs due to its superior thermal performance over air cooling. However, optimizing liquid cooling systems remains challenging due to the trade-off between heat transfer efficiency and pressure drop. Recent studies have explored various coolant selection, nanofluid enhancements, and complex channel geometries, an ideal balance remains difficult to achieve. While advanced methods such as topology optimization offer promising performance gains, they often introduce significant modeling and manufacturing complexity. In this study, we propose a practical alternative: an interconnected straight-channel cooling plate that introduces lateral passages to disrupt the thermal boundary layer and enhance mixing. Comparative analysis shows that the design improves temperature uniformity and reduces peak battery temperature, all while maintaining a moderate pressure drop. The proposed configuration offers a scalable and effective solution for next-generation BTMS, particularly in EV applications where thermal performance and manufacturability are both critical. Full article

Bamboo has evolved a highly optimized structural system in its culms, which this study transfers into lightweight fiber composite trusses fabricated by coreless filament winding. Focusing on the structural segmentation involving diaphragms of the biological role model, this design principle was integrated into the additive manufacturing process using a multi-stage winding, a tiling approach, and a water-soluble winding fixture. Through a FE-assisted analytical abstraction procedure, the transition to a carbon fiber material system was considered by determining a geometrical configuration optimized for structural mass, bending deflection, and radial buckling. Samples were fabricated from CFRP and experimentally tested in four-point bending. In mass-specific terms, integrating diaphragms into wound fiber composite samples improved failure load by 36%, ultimate load by 62%, and energy absorption by a factor of 7, at a reduction of only 14% in stiffness. Benchmarking against steel and PVC demonstrated superior mass-specific performance, although mōsō bamboo still outperformed all technical solutions, except in energy absorption. Full article

The aim of this study is to evaluate the technical performance and resilience of a Hybrid Renewable Energy System (HRES), designed to achieve water and energy autonomy on a Skyros Island, Greece. The system integrates renewable energy sources with multiple storage technologies. A high-resolution, 30-min simulation was developed, incorporating 10 years of historical weather data to model the operation of an HRES, which consists of wind turbines, photovoltaics, pumped hydro storage, and green hydrogen production. Reverse osmosis was used for desalination, and extended low-wind conditions were simulated to assess system resilience. Results indicate that the proposed system is, in fact, capable of meeting 89% of the annual energy demand and 99.99% of freshwater requirements by means of desalination. Wind power accounted for 53% of the total energy production, photovoltaics 2%, while pumped hydro and hydrogen storage contributed 17% and 6%, respectively. During artificially imposed windless periods, short-term deficits were addressed by the use of pumped hydro, while hydrogen ensured supply continuity in the final days, thereby demonstrating their complementary function. In this resilience stress-test, the system remained operational for 10 days during an artificial windless period, demonstrating the critical role of hybrid storage. The findings indicate that a combination of renewable energy with diversified storage and water management strategies can provide a reliable and self-sufficient water–energy nexus for remote islands. Finally, the novelty of this research work lies in the statistical analysis of calm-wind events and the development of the corresponding power-law relationship, conducted under the framework of the 30-min simulation. Full article

The main objective of this article is to model, simulate, and analyze the interaction of energy storage systems with BIPV installations. Currently, due to the instability of energy generation, the economic challenges of integrating PV installations into the electricity grid, and the desire to increase self-consumption, energy storage facilities are becoming increasingly popular. Subsidy programs most often favor PV installations, including BIPV, that work with energy storage devices. Therefore, there is a justified need to model energy storage devices for use with BIPV. The article describes the rationale for the benefits of using energy storage systems within current billing models, using Poland as an example. The introduction also provides an overview of the most popular energy storage technologies compatible with renewable energy installations. To achieve these objectives, appropriate system solutions were designed in the MATLAB environment and used to perform simulations, taking into account variable energy demand. An economic analysis of the system’s operation was conducted using a prosumer net-billing model, and adjustments were made to the system configuration. It has been shown that the use of appropriate energy storage solutions, cooperating with photovoltaic installations, allows for increased self-consumption and more efficient management of electricity obtained in BIPV, which has a positive impact on the payback time and economic profits. The analysis method used and the results obtained are true for the assumed known load profile; however, the method can be successfully applied to various load profiles. Full article

In power systems with a high penetration of renewable energy, integrating battery energy storage systems can enhance frequency regulation capabilities. However, in “islanded” operation mode, the lack of large grid interconnection support may cause significant frequency fluctuations or even instability when the system faces fault disturbances. To ensure the dynamic stability of the grid-forming energy storage system, this paper proposes a virtual synchronous machine (VSM) control parameter tuning and adaptive switching strategy. A control model is developed, which incorporates virtual inertia, damping, droop control, and transient virtual impedance. An optimization model for control parameter tuning is established for two typical disturbances: generator disconnection and three-phase symmetrical short-circuit fault. Additionally, a control parameter adaptive switching mechanism is designed based on voltage threshold and recovery time criteria. The application of this method to a simulation of an islanded power system demonstrates that high damping (e.g., greater than 15 pu) is suitable for generator disconnection disturbances, while a combination of low inertia (0.1 s) and high damping (50 pu) is appropriate for three-phase short-circuit disturbances. The control parameter tuning for three independent and aggregated scenarios successfully achieves effective frequency support. The adaptive switching criteria are set with a voltage threshold of 0.4 pu and a recovery time of 2 s, ensuring that the system frequency recovers within the specified range (48.5–51.5 Hz) within 1 s under short-circuit disturbance. The proposed method shows great potential for improving the operational stability of grid-forming energy storage systems. Full article

Building energy consumption is a major source of carbon emissions, with the heating energy demand of rural buildings in the hot summer and cold winter (HSCW) zone having increased 575-fold over the past 15 years. This research investigated an optimized solar–air source heat pump (SASHP) system to meet the heating demand of rural residences in this region. First, a typical rural building model was developed using SketchUp, and its heating load was simulated using TRNSYS, revealing an average load of 3.38 kW and a peak load of 5.9 kW. Based on the latest technical standards, the SASHP system was designed and simulated using TRNSYS, achieving an overall coefficient of performance (COP) of 3.67 while maintaining indoor thermal comfort within ISO 7730 Category II. Subsequently, the system was optimized through GenOpt to minimize the annual equivalent cost, yielding key parameters: a 15 m² solar collector at a 40.75° tilt, a 0.35 m³ water tank, and a 10.16 kW air source heat pump. Compared with the initial design, the optimized configuration achieved reductions of 35.60% in initial investment and 32.68% in annual equivalent costs. By ensuring thermal comfort and overcoming the economic barrier, this study provides a viable pathway for adoption and promotion of renewable heating technology in rural areas. Full article