Search Results (659)

This paper presents a high-fidelity multi-physics dynamic model for electric vehicles, serving as a fundamental building block for intelligent vehicle-to-grid (V2G) integration systems. The model accurately captures complex vehicle dynamics of the powertrain, battery, and regenerative braking, enabling precise energy consumption evaluation, including in AI-driven V2G scenarios. Validated using real-world data from a Citroën Ami operating on urban routes in Naples, Italy, it achieved exceptional accuracy with a root mean square error (RMSE) of 1.28% for dynamic state of charge prediction. This robust framework provides an essential foundation for AI-driven digital twin technologies in V2G applications, significantly advancing sustainable transportation and smart grid integration through predictive simulation. Its versatility supports diverse fleet applications, from residential energy management and coordinated charging optimization to commercial car sharing operations, leveraging backup power during peak demand or grid outages, so to maximize distributed battery storage utilization. Full article

The H1N1 swine influenza viruses CQ91 and CQ445, isolated from pigs in China, exhibited distinct virulence in mice despite sharing similar genomic constellations. CQ91 demonstrated higher pathogenicity (MLD₅₀: 5.4 log₁₀ EID₅₀) and replication efficiency in mice compared to CQ445 (MLD₅₀: 6.6 log₁₀ EID₅₀). Through reverse genetics, we found that the attenuation of CQ445 was due to a single substitution of glutamic acid (E) with lysine (K) at position 343 in the PB2 protein. Introducing the CQ445-PB2 (343K) into CQ91 significantly reduced viral replication and pathogenicity in mice, while replacing CQ445-PB2 with CQ91-PB2 (343E) restored virulence. In vitro studies showed that the K343E mutation impaired viral replication in MDCK and A549 cells and reduced polymerase activity in minigenome assays. Mechanistically, the amino acid at position 343 in the PB2 affects the transcription stage of the viral replication process. Structural modeling indicated that the charge reversal caused by E343K altered local electrostatic interactions without major conformational changes. Phylogenetic analysis revealed that PB2-343E is highly conserved (>99.9%) in human and swine H1/H3 influenza viruses, suggesting that PB2-343E confers an adaptive advantage. This study identifies PB2-343E as a critical determinant of influenza virus pathogenicity in mammals, highlighting its role in host adaptation. Full article

The one-dimensional (1D) Sb(III)-based organic–inorganic hybrid perovskite (AImd)₂¹_∞[SbI₅] (AImd = 1-allylimidazolium) crystallizes in the orthorhombic, centrosymmetric space group Pnma. The structure consists of corner-sharing [SbI₆] octahedra forming 1D chains separated by allylimidazolium cations. Void analysis through Mercury CSD software confirmed a densely packed lattice with a calculated void volume of 1.1%. Integrated quantum theory of atoms in molecules (QTAIM) and non-covalent interactions index (NCI) analyses showed that C–H···I interactions between the cations and the ¹_∞[SbI₅]²⁻ network predominantly stabilize the supramolecular assembly followed by N–H···I hydrogen bonds. The calculated growth morphology (GM) model fits very well to the experimental morphology. UV–Vis diffuse reflectance spectroscopy allowed us to determine the optical band gap to 3.15 eV. Density functional theory (DFT) calculations employing the B3LYP, CAM-B3LYP, and PBE0 functionals were benchmarked against experimental data. CAM-B3LYP best reproduced Sb–I bond lengths, while PBE0 more accurately captured the HOMO–LUMO gap and the associated electronic descriptors. These results support the assignment of an inorganic-to-organic [Sb–I] → π* charge-transfer excitation, and clarify how structural dimensionality and cation identity shape the material’s optoelectronic properties. Full article

Background: This paper proposes a conceptual framework for a multifunctional mobility hub (MMH) that co-locates shared e-mobility services, urban logistics, and charging/storage infrastructure within a single site. Aimed at high-density European cities, the MMH model addresses current gaps in both research and practice, where multimodal mobility services, logistics, and energy are rarely planned in an integrated manner. Methods: A mixed-methods approach was applied, including a systematic literature review (PRISMA), expert interviews, case studies, and a stakeholder workshop, to identify synergies across fleet types and operational domains. Results: The analysis reveals key design principles for MMHs, such as interoperable charging, the functional separation of passenger and freight flows, and modular, scalable infrastructure adapted to urban constraints. Conclusions: The MMH serves as a preliminary concept for planning next-generation mobility stations. It offers qualitative insights for urban planners, operators, and policymakers into how multifunctional hubs may support lower emissions, more efficient operations, and shared infrastructure use. Full article

This paper presents a low-power data acquisition (DAQ) chip tailored for impulsive charge sensing, featuring a comparator-gated dynamic acquisition (CG-DAQ) architecture. A dynamic comparator triggers both the gain stage and a 12-bit successive-approximation register (SAR) analog-to-digital converter (ADC) through a shared timing path, enabling event-driven amplification and digitization. Programmable conversion gain ranging from 5 to 40 mV/pC is achieved by switching the sampling capacitance. Fabricated in TSMC 65 nm CMOS, the chip detects input charges from 0.01 to 36 pC, supports a signal bandwidth of 10 kHz to 100 kHz, and enables sampling rates up to 1 MS/s. It achieves an input-referred noise of 5.5 fC_rms and a peak signal-to-noise ratio (SNR) of 67 dB, all within a 54 μW power envelope and a compact 0.03 mm² core area. The proposed architecture facilitates accurate and energy-efficient charge-domain sensing for capacitive and piezoelectric sensor applications. Full article

The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in 2023 (33% market share), faces infrastructure gaps constraining further growth. China is strategically mitigating CO₂ emissions while fostering economic expansion, notwithstanding constraints such as suboptimal battery technology advancements, elevated production expenditure, and enduring ecological impacts. This Political, Economic, Social, Technological, Legal, Environmental (PESTLE) assessment, operationalized through a survey of 800 stakeholders and Statistical Package for the Social Sciences IBM SPSS SPSS (Version 28) quantitative analysis (factor loading = 0.73 for Technology; eigenvalue = 4.12), identifies infrastructure gaps as the dominant barrier (72% of stakeholders). Political factors (β = 0.82) emerged as the strongest adoption predictor, outweighing economic subsidies in significance. The adoption of EVs in China presents a significant prospect for reducing CO₂ emissions and advancing technology. However, economic barriers, market dynamics, inadequate infrastructure, regulatory uncertainty, and social acceptance issues are addressed in the assessment. The study recommends prioritizing infrastructure investment (e.g., 500 K fast-charging stations by 2027) and policy stability to overcome adoption barriers. This study provides three key advances: (1) quantification of PESTLE factor weights via factor analysis, revealing technological (infrastructure) and political factors as dominant; (2) identification of infrastructure gaps, not subsidies, as the primary adoption barrier; and (3) demonstration of infrastructure’s persistence post-subsidy cuts. These insights redefine EV adoption priorities in China. Full article

The transportation sector in South Asia largely depends on internal combustion engine (ICE) vehicles, which are responsible for a large share of greenhouse gas (GHG) emissions, air pollution, and the increase in fuel prices. Although hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and fully electric vehicles (EVs) constitute promising alternatives, the rate of their implementation is low due to factors such as the high initial investment, the absence of the required infrastructure, and the reliance on fossil fuel-based electricity. This study is the first of its kind to examine Bangladesh’s drivetrain options in a comprehensive way, with in-depth real-world emission testing and economic analysis as the main tools of investigation into the environmental and economic feasibility of different technologies used in the vehicles available in Bangladesh, including lifecycle costs and infrastructure constraints. The study findings have shown that hybrid and plug-in hybrid vehicles are the best options, since they have moderate emissions and cost efficiency, respectively. Fully electric vehicles, however, face two main challenges: the overall lack of charging infrastructure and the overall high purchase prices. Among the evaluated technologies, PHEVs exhibited the lowest environmental and economic burden. The Toyota Prius PHEV emitted 98% less NOx compared to the diesel-powered Pajero Sport and maintained the lowest per-kilometer cost at BDT 6.39. In contrast, diesel SUVs emitted 178 ppm NOx and cost 22.62 BDT/km, reinforcing the transitional advantage of plug-in hybrid technology in Bangladesh’s context. Full article

The increasing share of electric vehicles (EVs) offers many advantages, including a reduced CO₂ footprint over the vehicles’ lifetime and improved resource efficiency through the recycling of high-voltage batteries. At the same time, the growing EV share presents challenges, such as ensuring sufficient power supply for the simultaneous charging of EVs within existing distribution grids. The scientific community has conducted numerous studies on the interaction between EVs and distribution grids, employing increasingly complex modeling techniques. However, the benefits of more complex modeling are rarely quantified. This study aims to address this gap by evaluating the impact of modeling complexity on transformer peak loads and busbar voltage for three communities with real-world distribution grid data. Since numerous stochastic factors influence EV charging patterns, this paper introduces a modular framework that accounts for the interconnection of these factors through microsimulation. The framework models charging events of battery electric vehicles (BEVs) and comprises modules for synthetic population generation, weekly mobility pattern assignment, and energy demand modeling based on vehicle class and ambient conditions. The findings reveal that cost-optimized charging strategies and seasonal factors, such as cold weather, have a significantly greater impact on the distribution grid than the detailed modeling of sociodemographic mobility patterns or detailed modeling of a diversified vehicle fleet. Full article

The article presents issues related to the melting of cast iron with a limited or zero share of pig iron in the charge. The results of melts conducted in electric induction furnaces are presented. The elimination of pig iron and its replacement with steel or return scrap is highly significant in the context of sustainable production and product life cycle assessment (LCA). The paper presents the results of research carried out during melts conducted under both laboratory and industrial conditions. The chemical composition of the cast iron, its physicochemical properties obtained from the analysis of the cooling curve and its derivative, as well as the structure, were analyzed. It was found that cast iron produced using high-quality steel scrap contains fewer sulfur and phosphorus impurities. However, it was also observed that such cast iron exhibits reduced nucleation ability, which can be improved by applying an inoculation process. Full article

In space, high-energy particle radiation poses a serious threat to the data stability and reliability of SRAM. Existing radiation-tolerant techniques, such as Triple Modular Redundancy (TMR) and Error Correction Code (ECC), have disadvantages such as large area, high power consumption, and additional delay, making them unsuitable for small satellite systems. To overcome these limitations, this paper proposes a 16-transistor-based radiation-tolerant SRAM cell, WRTU-16T, which applies a read-decoupled structure and a charge-sharing suppression mechanism. The proposed structure effectively isolates the storage node from external disturbances and improves the recovery capability for single-event inversion (SEU) and multiple-node inversion (SEMNU) by reducing charge loss. WRTU-16T shows superior performance in terms of write delay, charge recovery capability (Qc), hold power, and word line write threshold voltage (WWTV) compared to existing radiation-tolerant SRAM designs. The integrated circuit is implemented using a 90 nm CMOS process and has an operating voltage of 1V. Full article

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are linked by shared genetic mutations and overlapping clinical features, forming a clinical spectrum. This systematic review and meta-analysis analysed 97 studies, including 3212 patients with key ALS/FTD gene mutations, to identify gene-specific behavioural profiles. Chromosome 9 open reading frame 72 (C9orf72) mutations were strongly associated with psychotic symptoms and aggression, while superoxide dismutase 1 (SOD1) mutations had minimal cognitive effects. Progranulin (PGRN) mutations correlated with apathy and hallucinations, microtubule-associated protein tau (MAPT) mutations with disinhibition, and charged multivesicular body protein 2B (CHMP2B) with social impairments. Fused in sarcoma (FUS) mutations caused early sleep disturbances, TANK-binding kinase 1 (TBK1) led to disinhibition, and presenilin 1 and 2 (PSEN1/2) was linked to severe aggression. Prodromal cognitive changes in PGRN, MAPT, and CHMP2B mutations suggested early disease onset. Despite overlapping symptoms and clinical heterogeneity, understanding gene-specific patterns could inform tailored care strategies to enhance the quality of life for ALS and FTD patients. This study calls for refined guidelines integrating genetic behavioural profiles to improve patient and family support. Full article

This paper analyzes the impact of electromobility on distribution grids and voltage stability. In line with current legislation and the European Commission’s plans for the future of electromobility, the aim is to increase the share of electric vehicles to 50% by 2050. However, achieving this target can be challenging due to the characteristics and features of the electric vehicle charging stations and the associated charging methods, which can lead to constraints within the network. The analysis includes the integration of single-phase and three-phase chargers on a radial feeder, as well as the determination of the maximum number of vehicles that can be accommodated on a given feeder without compromising voltage stability. Five scenarios are evaluated using the DigSilent software package to gain a better understanding of the impact of electromobility on the distribution grid. Full article

The growing integration of renewable energy and electric vehicle loads in parks has intensified the intermittency of photovoltaic (PV) output and demand-side uncertainty, complicating energy storage system design and operation. Meanwhile, under carbon neutrality goals, the energy system must balance economic efficiency with emission reductions, raising the bar for storage planning. To address these challenges, this study proposes a two-stage robust optimization method for shared energy storage configuration in a park-level integrated PV–storage–charging system (PV-SESS-CS). The method considers the uncertainties of PV and electric vehicle (EV) loads and incorporates carbon emission reduction benefits. First, a configuration model for shared energy storage that accounts for carbon emission reduction is established. Then, a two-stage robust optimization model is developed to characterize the uncertainties of PV output and EV charging demand. Typical PV output scenarios are generated using Latin Hypercube Sampling, and representative PV profiles are extracted via K-means clustering. For EV charging loads, uncertainty scenarios are generated using Monte Carlo Sampling. Finally, simulations are conducted based on real-world industrial park data. The results demonstrate that the proposed method can effectively mitigate the negative impact of source-load fluctuations, significantly reduce operating costs, and enhance carbon emission reductions. This study provides strong methodological support for optimal energy storage planning and low-carbon operation in park-level PV-SESS-CS. Full article

The development of electric mobility offers new perspectives in the energy sector and improves resource efficiency and sustainability. This paper proposes a new strategy for synchronizing the energy requirements of home, commercial, and vehicle mobility, with a focus on the batteries of electric cars. In particular, this paper describes the coordination between a battery management algorithm that optimally assigns its capacity so that at least a part is reserved for mobility and a vehicle-to-building (V2B) service algorithm that uses a share of EV battery energy to improve user participation in renewable energy exploitation at home and at work. The system offers the user the choice of always maintaining a minimum charge for mobility or providing more flexible use of energy for business needs while maintaining established vehicle autonomy. Suitable management at home and at work allows always charging the vehicle to the required level of charge with renewable power excess, highlighting how the cooperation of home and work charging may provide novel frameworks for a smarter and more sustainable integration of electric mobility, reducing energy consumption and providing more effective energy management. The effectiveness of the proposed solution is demonstrated in a realistic configuration with real data and an experimental setup. Full article

This paper introduces a high-conversion ratio multiphase nonisolated converter built from generic LC cells. The unique architecture that hinges on a generic capacitor inductor switching module enables the high modularity of the topology, providing a quick extension of the converter design in an interleaved configuration for lower ripple and higher current output. The generic module comprises the basic power components of a nonisolated DC–DC converter, where the unique interaction between the capacitor and the inductor results in a soft charging operation, which curbs the losses of the converter, and contributes to a higher efficiency. Additional features of the new converter include a significantly extended effective duty ratio, and a lower voltage stress on the switches, a very high output current, and architecture-inherent output current sharing that balances the loading between the phases. In addition, a power extension using a paralleling and interleaving approach is presented to provide higher output current capabilities. Simulation and experimental results of a modular interleaved three-phase prototype demonstrate an excellent proof of concept and agree well with the theoretical analyzes developed in this study. Full article