Search Results (811)

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

As the popularity of electric vehicles (EVs) continues to increase, the need for effective and efficient driveline lubricants and dielectric coolants has become crucial. Commercially used mineral oils or synthetic ester-based coolants, despite performing satisfactorily, are not environmentally friendly. The fatty esters of vegetable oils, after overcoming their shortcomings (like poor oxidative stability, higher viscosity, and pour point) through chemical modification, have recently been used as potential dielectric coolants in transformers. The benefits of natural esters, including a higher flash point, breakdown voltage, dielectric character, thermal conductivity, and most importantly, readily biodegradable nature, have made them a suitable and sustainable substitute for traditional coolants in electric transformers. Based on their excellent performance in transformers, research on their application as dielectric immersion coolants in modern EVs has been emerging in recent years. This review primarily highlights the beneficial aspects of natural esters performing dual functions—cooling as well as lubricating, which is necessary for “wet” e-motors in EVs—through a comparative study with the commercially used mineral and synthetic coolants. The adoption of natural fatty esters of vegetable oils as an immersion cooling fluid is a significant sustainable step for the battery thermal management system (BTMS) of modern EVs considering environmental safety protocols. Continued research and development are necessary to overcome the ongoing challenges and optimize esters for widespread use in the rapidly expanding electric vehicle market. Full article

Biopolymers and bio-based plastics, such as polylactic acid (PLA) and polybutylene succinate (PBS), are recognized as environmentally friendly materials and are widely used, especially in the packaging industry. The purpose of this study was to assess the degradation of PLA- and PBS-based formulations in the forms of granules and films under controlled composting conditions at a laboratory scale. Biodegradation tests of bio-based materials were conducted under controlled aerobic conditions, following the standard EVS-EN ISO 14855-1:2012. Scanning electron microscopy (SEM) was performed using a high-resolution Zeiss Ultra 55 scanning electron microscope to analyze the samples. After the six-month laboratory-scale composting experiment, it was observed that the PLA-based materials degraded by 47.46–98.34%, while the PBS-based materials exhibited a final degradation degree of 34.15–80.36%. Additionally, the PLA-based compounds displayed a variable total organic carbon (TOC) content ranging from 38% to 56%. In contrast, the PBS-based compounds exhibited a more consistent TOC content, with a narrow range from 53% to 54%. These findings demonstrate that bioplastics can contribute to reducing plastic waste through controlled composting, but their degradation efficiency depends on the material composition and environmental conditions. Future efforts should optimize bioplastic formulations and composting systems while developing supportive policies for wider adoption. Full article

Accurately predicting how quickly people will adopt electric vehicles (EVs) is vital for planning charging stations, managing supply chains, and shaping climate policy. We present a forecasting model that uses three separate Long Short-Term Memory (LSTM) branches—one for past EV sales, one for infrastructure and policy signals, and one for economic trends. An attention mechanism first highlights the most important weeks in each branch, then decides which branch matters most at any point in time. Trained end-to-end on publicly available data, the model beats traditional statistical methods and newer deep learning baselines while remaining small enough to run efficiently. An ablation study shows that every branch and both attention steps improve accuracy, and that adding policy and economic data helps more than relying on EV history alone. Because the network is modular and its attention weights are easy to interpret, it can be extended to produce confidence intervals, include physical constraints, or forecast adoption of other clean-energy technologies. Full article

Indonesia’s worsening air pollution and traffic emissions have thrust electric vehicles (EVs) into the spotlight, but what really drives Indonesians to make the switch? This study integrates Protection Motivation Theory with green branding and policy frameworks to explain electric vehicle (EV) adoption in Indonesia. Using a nationwide survey (n = 986) and partial-least-squares structural-equation modeling, we test how environmental awareness, consumer expectancy, threat appraisal, and coping appraisal shape adoption both directly and through green brand image (GBI), while perceived policy incentives moderate the GBI–adoption link. The model accounts for 54% of the variance in adoption intention. These findings highlight that combining public awareness campaigns, compelling green brand messaging, and carefully calibrated policy incentives is essential for accelerating Indonesia’s transition to cleaner transport. Full article

This study evaluates the feasibility and visibility of electric vehicles (EVs) in Egypt, addressing critical research gaps and proposing actionable strategies to drive adoption. Employing a systematic review of academic, governmental, and industry sources, the paper identifies underexplored areas such as rural–urban adoption disparities, lifecycle assessments of EV batteries, and sociocultural barriers, including gender dynamics and entrenched consumer preferences. Its primary contribution is an interdisciplinary framework that integrates technical aspects, such as grid resilience and climate-related battery degradation, with socioeconomic dimensions, providing a holistic overview of EV feasibility in Egypt tailored to Egypt’s context. Key findings reveal infrastructure limitations, inconsistent policy frameworks, and behavioral skepticism as major hurdles, and highlight the untapped potential of renewable energy integration, particularly through synergies between solar PV generation (e.g., Benban Solar Park) and EV charging infrastructure. Recommendations prioritize policy reforms (e.g., tax incentives, streamlined tariffs), solar-powered charging infrastructure expansion, public awareness campaigns, and local EV manufacturing to stimulate economic growth. The study underscores the urgency of stakeholder collaboration to transform EVs into a mainstream solution, positioning Egypt as a regional leader in sustainable mobility and equitable development. Full article

Co_0.95R_0.05Fe₂O₄ nanoparticles were synthesized using a sol-gel approach incorporating bio-based agents and were found to be single phases adopting a cubic Fd-3m structure. XPS shows the presence of Gd³⁺ and Ho³⁺ ions. The spin–orbit splitting of about 15.4 eV observed in Co 2p core-level spectra is an indication that Co is predominantly present as Co³⁺ state, while the satellite structures located at about 6 eV higher energies than the main lines confirm the existence of divalent Co in Co_0.95R_0.05Fe₂O₄. The positions of the Co 3s and Fe 3s main peaks obtained by curve fitting and the exchange splitting obtained values for Co 3s and Fe 3s levels point to the high Co³⁺/Co²⁺ and Fe³⁺/Fe²⁺ ratios in both samples. The saturation magnetizations are smaller for the doped samples compared to the pristine ones. For theoretical magnetization calculation, we have considered that the heavy rare earths are in octahedral sites and their magnetic moments are aligned antiparallelly with 3d transition magnetic moments. ZFC-FC curves shows that some nanoparticles remain superparamagnetic, while the rest are ferrimagnetic, ordered at room temperature, and showing interparticle interactions. The M_S/Ms ratio at room temperature is below 0.5, indicating the predominance of magnetostatic interactions. Full article

Dark asphalt surfaces, absorbing about 95% of solar radiation and warming to 60–70 °C during summer, intensify urban heat while providing substantial prospects for energy extraction. This review evaluates four primary technologies—asphalt solar collectors (ASCs, including phase change material (PCM) integration), photovoltaic (PV) systems, vibration-based harvesting, thermoelectric generators (TEGs)—focusing on their principles, efficiencies, and urban applications. ASCs achieve up to 30% efficiency with a 150–300 W/m² output, reducing pavement temperatures by 0.5–3.2 °C, while PV pavements yield 42–49% efficiency, generating 245 kWh/m² and lowering temperatures by an average of 6.4 °C. Piezoelectric transducers produce 50.41 mW under traffic loads, and TEGs deliver 0.3–5.0 W with a 23 °C gradient. Applications include powering sensors, streetlights, and de-icing systems, with ASCs extending pavement life by 3 years. Hybrid systems, like PV/T, achieve 37.31% efficiency, enhancing UHI mitigation and emissions reduction. Economically, ASCs offer a 5-year payback period with a USD 3000 net present value, though PV and piezoelectric systems face cost and durability challenges. Environmental benefits include 30–40% heat retention for winter use and 17% increased PV self-use with EV integration. Despite significant potential, high costs and scalability issues hinder adoption. Future research should optimize designs, develop adaptive materials, and validate systems under real-world conditions to advance sustainable urban infrastructure. Full article

Tungsten and tungsten alloys are widely used in important industrial fields due to their high density, hardness, melting point, and corrosion resistance. However, machining often leaves processing marks on their surface, significantly affecting the surface quality of precision components in industrial applications. Electrolytic polishing offers high efficiency, low workpiece wear, and simple processing. In this study, an electrolytic polishing method is adopted and a novel trisodium phosphate–sodium hydroxide electrolytic polishing electrolyte is developed to study the effects of temperature, voltage, polishing time, and solution composition on the surface roughness of a tungsten–nickel–iron alloy. The optimal voltage, temperature, and polishing time are determined to be 15 V, 55 °C, and 35 s, respectively, when the concentrations of trisodium phosphate and sodium hydroxide are 100 g·L⁻¹ and 6 g·L⁻¹. In addition, glycerol is introduced into the electrolyte as an additive. The calculated LUMO value of glycerol is −5.90 eV and the HOMO value is 0.40 eV. Moreover, electron enrichment in the hydroxyl region of glycerol can form an adsorption layer on the surface of the tungsten alloy, inhibit the formation of micro-pits, balance ion diffusion, and thus promote the formation of a smooth surface. At 100 mL·L⁻¹ of glycerol, the roughness of the tungsten–nickel–iron alloy decreases significantly from 1.134 μm to 0.582 μm. The electrochemical polishing mechanism of the tungsten alloy in a trisodium phosphate electrolyte is further investigated and explained according to viscous film theory. This study demonstrates that the trisodium phosphate–sodium hydroxide–glycerol electrolyte is suitable for electropolishing tungsten–nickel–iron alloys. Overall, the results support the application of tungsten–nickel–iron alloy in the electronics, medical, and atomic energy industries. Full article

The increasing adoption of electric vehicles (EVs) requires efficient management of charging infrastructure, particularly in optimizing the allocation of limited charging resources. This paper addresses the preemptive electric vehicle charging scheduling problem (EVCSP), where charging sessions can be interrupted to maximize the number of satisfied demands. The existing mathematical formulations often struggle with scalability and computational efficiency for even small problem instances. As a result, we propose an enhanced mathematical programming model, which is further refined to reduce decision variable complexity and improve computational performance. In addition, a constraint programming (CP) approach is explored as an alternative method for solving the EVCSP due to its strength in handling complex scheduling constraints. The experimental results demonstrate that the developed methods significantly outperform the existing models in the literature, providing scalable and efficient solutions for optimizing EV charging infrastructure. Full article

This study introduces a novel tripartite evolutionary game model to analyze the strategic interactions among electric vehicle (EV) aggregators, local governments, and EV users in vehicle–grid interaction (VGI) markets. The core novelty lies in capturing bounded rationality and dynamic decision-making across the three stakeholders, revealing how policy incentives and market mechanisms drive the transition from disordered charging to bidirectional VGI. Key findings include the following: (1) The system exhibits five stable equilibrium points, corresponding to three distinct developmental phases of the VGI market: disordered charging (V0G), unidirectional VGI (V1G), and bidirectional VGI (V2G). (2) Peak–valley price differences are the primary driver for transitioning from V0G to V1G. (3) EV aggregators’ willingness to adopt V2G is influenced by upgrade costs, while local governments’ subsidy strategies depend on peak-shaving benefits and regulatory costs. (4) Increasing the subsidy differential between V1G and V2G accelerates market evolution toward V2G. The framework offers actionable policy insights for sustainable VGI development, while advancing evolutionary game theory applications in energy systems. Full article

The transition to electric vehicles (EVs) is accelerating due to global efforts to reduce greenhouse gas emissions and reliance on fossil fuels. Lithium-ion batteries (LIBs) are the predominant energy storage solution in EVs, offering high energy density, efficiency, and long lifespan. However, their adoption is overly involved with critical safety concerns, including thermal runaway and overheating. This review systematically focuses on the critical role of battery thermal management systems (BTMSs), such as active, passive, and hybrid cooling systems, in maintaining LIBs within their optimal operating temperature range, ensuring temperature homogeneity, safety, and efficiency. Additionally, the study explores the impact of integrating artificial intelligence (AI) and machine learning (ML) into BTMS on thermal performance prediction and energy-efficient cooling, focusing on optimizing the operating parameters of cooling systems. This review provides insights into enhancing LIB safety and performance for widespread EV adoption by addressing these challenges. Full article

Before the onset of global warming concerns, the idea of manufacturing electric vehicles on a large scale was not widely considered. However, electric vehicles offer several advantages that have garnered attention. They are environmentally friendly, with simpler drive systems compared to traditional fossil fuel vehicles. Additionally, electric vehicles are highly efficient, with an efficiency of around 90%, in contrast to fossil fuel vehicles, which have an efficiency of about 30% to 35%. The higher energy efficiency of electric vehicles contributes to lower operational costs, which, alongside regulatory incentives and shifting consumer preferences, has increased their strategic importance for many vehicle manufacturers. In this paper, we present a thematic literature review on electric vehicles charging station location planning and scheduling. A systematic literature review across various data sources in the area yielded ninety five research papers for the final review. The research results were analyzed thematically, and three key directions were identified, namely charging station deployment and placement, optimal allocation and scheduling of EV parking lots, and V2G and smart charging systems as the top three themes. Each theme was further investigated to identify key topics, ongoing works, and future trends. It has been found that optimization methods followed by simulation and multi-criteria decision-making are most commonly used for EV infrastructure planning. A multistakeholder perspective is often adopted in these decisions to minimize costs and address the range anxiety of users. The future trend is towards the integration of renewable energy in smart grids, uncertainty modeling of user demand, and use of artificial intelligence for service quality improvement. Full article

Electric vehicles (EVs) offer a sustainable solution for reducing carbon emissions in the transportation sector. However, their increasing widespread adoption poses significant challenges for local distribution grids, many of which were not designed to accommodate the heightened and irregular power demands of EV charging. Components such as transformers and distribution networks may experience overload, voltage imbalances, and congestion—particularly during peak periods. While upgrading grid infrastructure is a potential solution, it is often costly and complex to implement. The unpredictable nature of EV charging behavior further complicates grid operations, as charging demand fluctuates throughout the day. Therefore, efficient integration into the grid—both for charging and potential discharging—is essential. This paper reviews recent studies on the impacts of high EV penetration on distribution grids and explores various strategies to enhance grid performance during peak demand. It also examines promising optimization methods aimed at mitigating negative effects, such as load shifting and smart charging, and compares their effectiveness across different grid parameters. Additionally, the paper discusses key challenges related to impact analysis and proposes approaches to improve them in order to achieve better overall grid performance. Full article

The present study adopts the social constructivism theory and consumer decision-making process model with the aim of examining the social identity that consumers build through the purchase of electric vehicles (EVs) in line with their income, age, gender, and education. The study’s findings indicate that this social identity, shaped by income, age, gender and education, exerts a significant influence on consumer decision-making behavior. This identity is shaped not only by the make and model of EVs chosen, but also by their preferences for vehicle performance and technical features. The adoption of EVs by consumers is driven by dual objectives: the fulfilment of practical needs and the shaping of social identities in social interactions that correspond to their income, age, gender, and education. The study’s findings are of significant value in understanding the social identity aspirations of consumers in the electric vehicle consumer market, and provide a theoretical foundation for future electric vehicle companies to create products and corporate cultures that meet their target customers, thereby effectively promoting the popularization of electric vehicles. Full article