Search Results (5,924)

Background/Objectives: In soccer, scanning before receiving the ball helps players better perceive and interpret their surroundings, enabling faster and more effective passes. Despite its importance, no standardized tests currently incorporate scanning actions into assessments of passing abilities. In this study, we test the reliability and validity of a battery of passing tests that assess a player’s ability to control and pass the ball while also scanning for the appropriate target. Methods: We designed three passing tests that reflect different scanning demands that are routinely placed upon players during matches. Using players from the first and reserve teams of two professional clubs in Ghana (Club A, first-team n = 11, reserve-team n = 10; Club B, first-team n = 16, reserve-team n = 17), we: (i) tested the repeatability of each passing test (intraclass correlations), (ii) assessed whether the tests could distinguish between first and reserve team players (linear mixed-effects model), and (iii) examined whether players who were better in the passing tests had higher performances in 3v1 Rondo possession games (linear models). Results: All passing tests were significantly repeatable (ICCs = 0.77–0.85). Performance was highest in the 120-degree test (30.11 ± 7.22 passes/min), where scanning was not required, and was lowest in the 360-degree test (25.55 ± 5.94 passes/min), where players needed to constantly scan behind them. When players were scanning through an arc of 180 degrees, their average performance was 27.41 ± 6.14 passes/min. Overall passing performance significantly distinguished first from reserve team players (β = −1.47, t (51) = −4.32, p < 0.001)) and was positively associated with 3v1 Rondo possession performance (R² = 0.51, p < 0.001). Conclusions: Our results show that these passing tests are reliable, distinguish players across competitive levels, and correlate with performance in possession games. These tests offer a simple, ecologically valid way to assess scanning and passing abilities for elite players. Full article

Over the past few decades, lithium-ion batteries (LIBs) have gained significant attention due to their inherent potential for environmental sustainability and unparalleled energy storage efficiency. Meanwhile, polymer electrolytes have gained popularity in several fields due to their ability to adapt to various battery geometries, enhanced safety features, greater thermal stability, and effectiveness in reducing dendrite growth on the anode. However, their relatively low ionic conductivity compared to liquid electrolytes has limited their application in high-performance devices. This limitation has led to recent studies revolving around the development of poly(ionic liquids) (PILs), particularly imidazolium-mediated polymer backbones as novel electrolyte materials, which can increase the conductivity with fine-tuning structural benefits, while maintaining the advantages of both solid and gel electrolytes. In this study, a curated dataset of 120 data points representing eight different polymers was used to predict ionic conductivity in imidazolium-based PILs as well as the emerging ionene substructures. For this purpose, four ML models: CatBoost, Random Forest, XGBoost, and LightGBM were employed by incorporating chemical structure and temperature as the models’ inputs. The best-performing model was further employed to estimate the conductivity of novel ionenes, offering insights into the potential of advanced polymer architectures for next-generation LIB electrolytes. This approach provides a cost-effective and intelligent pathway to accelerate the design of high-performance electrolyte materials. Full article

Graphite has been recognized as a critical material by the United States (US), the European Union (EU), and Australia. Owing to its unique structure and properties, it is utilized in many industries and has played a key role in the clean energy sector, particularly in the lithium-ion battery (LIB) industries. With the projected increase in global graphite demand, driven by the shift to clean energy and the use of EVs, as well as the geographically concentrated production and reserves of natural graphite, interest in graphite recycling has increased, with a specific focus on using spent LIBs and other waste carbon material. Although most established and developing LIB recycling technologies are focused on cathode materials, some have started recycling graphite, with promising results. Based on the different secondary sources and recycling paths reported, hydrometallurgy-based treatment is usually employed, especially for the purification of graphite; greener alternatives are being explored, replacing HF both in lab-scale research and in industry. This offers a viable solution to resource dependency and mitigates the environmental impact associated with graphite production. These developments signal a trend toward sustainable and circular pathways for graphite recycling. Full article

This study investigates the impact of Time-of-Use (TOU) scheduling and battery energy storage systems (BESS) on voltage stability in a typical Malaysian medium-voltage distribution network with high photovoltaic (PV) system penetration. The analyzed network comprises 110 nodes connected via eight feeders to a pair of 132/11 kV, 15 MVA transformers, supplying a total load of 20.006 MVA. Each node is integrated with a 100 kW PV system, enabling up to 100% PV penetration scenarios. A hybrid mitigation strategy combining TOU-based load shifting and BESS was implemented to address voltage violations occurring, particularly during low-load night hours. Dynamic simulations using DIgSILENT PowerFactory were conducted under worst-case (no load and peak load) conditions. The novelty of this research is the use of real rural network data to validate a hybrid BESS–TOU strategy, supported by detailed sensitivity analysis across PV penetration levels. This provides practical voltage stabilization insights not shown in earlier studies. Results show that at 100% PV penetration, TOU or BESS alone are insufficient to fully mitigate voltage drops. However, a hybrid application of 0.4 MWh BESS with 20% TOU load shifting eliminates voltage violations across all nodes, raising the minimum voltage from 0.924 p.u. to 0.951 p.u. while reducing active power losses and grid dependency. A sensitivity analysis further reveals that a 60% PV penetration can be supported reliably using only 0.4 MWh of BESS and 10% TOU. Beyond this, hybrid mitigation becomes essential to maintain stability. The proposed solution demonstrates a scalable approach to enable large-scale PV integration in dense rural grids and addresses the specific operational characteristics of Malaysian networks, which differ from commonly studied IEEE test systems. This work fills a critical research gap by using real local data to propose and validate practical voltage mitigation strategies. Full article

A continuous mixing process with a twin-screw extruder was investigated for graphite-based negative electrode pastes for high-power applications. In the extrusion-based mixing process, the first kneading concentration is one of the key processing parameters for systematic optimization of relevant electrode paste properties like viscosity and particle size distribution. For different active materials at a constant electrode paste composition, a clear correlation of increasing kneading concentration with decreasing viscosity can be observed up to a certain reversal point, initiating a change in the trend and the rheological behavior, thus indicating a process limit. The fundamental effects causing this change and the associated impact on materials and battery performance were evaluated by applying further analytical methods and electrochemical characterization. It is revealed that the change in viscosity is associated with enhanced de-agglomeration of the carbon black additive and with partial particle grinding of the active material and thus a partial change in the interlayer distance of graphene layers and, correspondingly, the electrochemical behavior of the active material. Beyond this, correlations between processing parameters and product properties are presented. Furthermore, indicators are suggested with which monitoring of the machine parameters enables the detection of changes in the electrode paste characteristics. Full article

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

In order to achieve the goals of carbon neutrality, large-scale storage of renewable energy sources has been integrated into the power grid. Under these circumstances, the power grid faces the challenge of peak shaving. Therefore, this paper proposes a coordinated variable-power control strategy for multiple battery energy storage stations (BESSs), improving the performance of peak shaving. Firstly, the strategy involves constructing an optimization model incorporating load forecasting, capacity constraints, and security indices to design a coordination mechanism tracking the target load band with the equivalent power. Secondly, it establishes a quantitative evaluation system using metrics such as peak–valley difference and load standard deviation. Comparison based on typical daily cases shows that, compared with the constant power strategy, the coordinated variable-power control strategy has a more obvious and comprehensive improvement in overall peak-shaving effects. Furthermore, it employs a “dynamic dispatch of multiple BESS” mode, effectively mitigating the risks and flexibility issues associated with single BESSs. This strategy provides a reliable new approach for large-scale energy storage to participate in high-precision peaking. Full article

This study combines text mining and binary logit model to analyze the main influencing factors of consumers’ purchase intention for new energy vehicles (NEVs) in Urumqi. Through the analysis of 34,561 consumer reviews and 400 valid questionnaire data, the study found that battery technology, sales price, and policy support have a significant impact on purchase intention. Based on the differences in consumers’ price sensitivity, technology preference, and policy support, this paper segments consumers into six groups. Based on these findings, we propose policy recommendations to optimize subsidy policies, promote battery technology upgrades, and improve charging infrastructure, in order to drive the development of the NEV market. Full article

The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and labor-intensive, hindering their large-scale production. Recent advances in 3D printing technology offer innovative pathways to address these challenges. By combining design flexibility with material optimization, 3D printing holds the potential to enhance battery performance and enable customized structures. This review systematically examines the application of 3D printing technology in fabricating key AZIB components, including electrodes, electrolytes, and integrated battery designs. We critically compare the advantages and disadvantages of different 3D printing techniques for these components, discuss the potential and mechanisms by which 3D-printed structures enhance ion transport and electrochemical stability, highlight critical existing scientific questions and research gaps, and explore potential strategies for optimizing the manufacturing process. Full article

We report an investigation on the cobalt(II) chelation mechanism by a modified α-maltoside ligand 9 decorated with two iminodiacetate (IDA) residues on C6,C6′ positions. Herein we uncovered the capacity of this biodegradable ligand to chelate cobalt(II), an ionic metal contaminant in the environment that is used, in particular, in lithium-ion batteries. The interactions between cobalt(II) and synthesized ligand 9 were systematically studied using different analytical methods such as ¹H and ¹³C NMR, potentiometry, spectrophotometry, ITC, and ICP-AES. We observed a high affinity for the 1:1 complex, one cobalt(II) associated with two iminodiacetate groups, which is 10-fold higher than the 2:1 complex, where each of the two IDA groups interacts alone with a cobalt(II). Taking into account the log β_CoL value obtained (≈12.3) with the stoichiometry 1:1, the strength of this complexation with cobalt(II) can be ranked as follows for the most common ligands: IDA < MIDA < NTA < 9 < EDTA < TTHA < DTPA. We further completed a preliminary remediation test with water contaminated with cobalt(II) and recovered cobalt(II) metal using Chelex^® resin, which allowed a recycling of the synthetic ligand for future recovering experiments. The results shed light on the great potential of using this synthetic ligand as an effective and green remediation tool. Full article

The typical ranges available for electric vehicles (EVs) may be considered by users to be inadequate when compared to long, real-life trips, and charging operations may need to be planned along journeys. To evaluate the compatibility between vehicle features and charging options for realistic journeys performed by car, a simulation approach is proposed here, using travel data collected from real vehicles to obtain trip chains for multiple consecutive days. Car travel activities, including stops with the option of charging, were simulated by applying an agent-based approach. Charging operations can be integrated into trip chains for user activities, assuming that they remain unchanged in the event that vehicles switch to electric. The energy consumption of the analyzed trips, disaggregated by vehicle type, was estimated using the average travel speed, which is useful for capturing the main route features (ranging from urban to motorways). Data were recorded for approximately 25,000 vehicles in the Turin Metropolitan Area for six consecutive days. Market segmentation of the vehicles was introduced to take into consideration different energy consumption rates and charging times, given that the electric power, battery size, and consumption rate can be related to the vehicle category. Charging activities carried out using public infrastructure during idle time between consecutive trips, as well as those carried out at home or work, were identified in order to model different needs. Full article

Although particulate matter (PM) pollution from vehicles’ exhaust has decreased significantly over the years, the contribution from non-exhaust sources (brakes, tyres) has remained at the same levels. In the European Union (EU), Euro 7 regulation introduced PM limits for vehicles’ brake systems. Regenerative braking, i.e., recuperation of the deceleration kinetic and potential energy to the vehicle battery, is one of the strategies to reduce the brake emission levels and improve vehicle efficiency. According to the regulation, the shares of friction and regenerative braking can be determined with actual testing of the vehicle on a chassis dynamometer. In this study we tested the regenerative capabilities of a plug-in hybrid vehicle, both in the laboratory and on the road, under different protocols (including both smooth and aggressive braking) and covering a wide range of driving conditions (urban, rural, motorway) over 10,000 km of driving. Good agreement was obtained between laboratory and on-road tests, with the use of the friction brakes being on average 7% and 5.3%, respectively. However, at the same time it was demonstrated that the friction braking share can vary over a wide range (up to around 30%), depending on the driver’s behaviour. Full article

This study aims to develop an optimal underwriting strategy for affordable (H1 and M1) and premium (L1 and M2) electric vehicles (EVs), balancing financial risk and sustainability commitments. The research is motivated by regulatory pressures, risk management needs, and sustainability goals, necessitating an adaptation of traditional underwriting models. The study employs a modified Delphi method with industry experts to identify key risk factors, including accident risk, repair costs, battery safety, driver behavior, and PCAF carbon impact. A sensitivity analysis was conducted to examine premium adjustments under different risk scenarios, categorizing EVs into four risk segments: Low-Risk, Low-Carbon (L1); Medium-Risk, Low-Carbon (M1); Medium-Risk, High-Carbon (M2); and High-Risk, High-Carbon (H1). Findings indicate that premium EVs (L1 and M2) exhibit lower volatility in underwriting costs, benefiting from advanced safety features, lower accident rates, and reduced carbon attribution penalties. Conversely, budget EVs (H1 and M1) experience higher premium fluctuations due to greater accident risks, costly repairs, and higher carbon costs under PCAF implementation. The worst-case scenario showed a 14.5% premium increase, while the best-case scenario led to a 10.5% premium reduction. The study recommends prioritizing premium EVs for insurance coverage due to their lower underwriting risks and carbon efficiency. For budget EVs, insurers should implement selective underwriting based on safety features, driver risk profiling, and energy efficiency. Additionally, incentive-based pricing such as telematics discounts, green repair incentives, and low-carbon charging rewards can mitigate financial risks and align with net-zero insurance commitments. This research provides a structured framework for insurers to optimize EV underwriting while ensuring long-term profitability and regulatory compliance. Full article

Inspired by the Toyota Mirai, this study presents a high-fidelity data-driven approach for modelling and simulation of a fuel cell hybrid electric powertrain. This study utilises technical assessment data sourced from Argonne National Laboratory’s publicly available report, faithfully modelling most of the vehicle subsystems as data-driven entities. The simulation framework is developed in the MATLAB/Simulink environment and is based on a power dynamics approach, capturing nonlinear interactions and performance intricacies between different powertrain elements. This study investigates subsystem synergies and performance boundaries under a combined driving cycle composed of the NEDC, WLTP Class 3 and US06 profiles, representing urban, extra-urban and aggressive highway conditions. To emulate the real-world load-following strategy, a state transition power management and allocation method is synthesised. The proposed method dynamically governs the power flow between the fuel cell stack and the traction battery across three operational states, allowing the battery to stay within its allocated bounds. This simulation framework offers a near-accurate and computationally efficient digital counterpart to a commercial hybrid powertrain, serving as a valuable tool for educational and research purposes. Full article

Internal combustion engine vehicles damage the environment and public health by emitting toxic fumes, such as CO₂ or CO and other trace compounds. The use of electric cars helps to reduce the emission of pollutants into the environment due to the use of batteries with no direct and local emissions. However, accidents of battery electric vehicles pose new challenges, such as thermal runaway. Such accidents can be serious and, in some cases, may result in uncontrolled overheating that causes the battery pack to spontaneously ignite. In particular, the most dangerous vehicles are heavy goods vehicles (HGVs), as they release a large amount of energy that generate high temperatures, poor visibility, and respiratory damage. This study aims to determine the potential consequences of large BEV fires in road tunnels using computational fluid dynamics (CFD). Furthermore, a comparison between a BEV and an ICEV fire shows the differences related to the thermal and the toxic impact. Furthermore, the adoption of a longitudinal ventilation system in the tunnel helped to mitigate the BEV fire risk, keeping a safer environment for tunnel users and rescue services through adequate smoke control. Full article