Search Results (3,720)

Multirotor UAVs powered by batteries face limitations due to the low energy density of their energy source, which constitutes a significant portion of the total weight. During missions, the high battery mass remains constant, necessitating high required power. This leads to reductions in payload capacity and endurance constraints. This study developed a design tool for multirotor UAVs that sequentially detach used batteries during missions to reduce weight and extend endurance. The developed tool consists of a battery weight prediction model and a required power prediction model. It accurately predicts endurance by considering changes in weight, thrust, RPM, motor-propeller efficiency, and required power at each battery separation point. Using the developed tool, the battery separation technology was applied to a quadcopter with total weights of 7, 15, and 25 kg, and the extended endurances were quantitatively compared. The results showed endurance improvements of 127.3%, 122.0%, and 127.0% for the 7, 15, and 25 kg quadcopters, respectively, compared to using a single battery. In addition, the method was applied to the commercially available industrial UAV DJI Matrice 300 RTK. With a 2.7 kg payload, the two-stage battery configuration extended the endurance by 12.5% compared to the single-battery case. Under no-payload conditions, a three-stage configuration achieved a 16.7% improvement. These results confirm the effectiveness of staged battery detachment even in real-world UAV platforms. Full article

Hybrid Renewable Energy Systems (HRESs) can be an effective and sustainable way to provide electricity for remote and rural villages in Morocco; however, the design and optimization of such systems can be a challenging and difficult task. In this context, the objective of this research is to design and optimize different (HRESs) that incorporate various renewable energy technologies, namely Photovoltaics (PVs), wind turbines, and Concentrating Solar Power (CSP), whereas biomass generators and batteries are used as a storage medium. Overall, 15 scenarios based on different HRES configurations were designed, simulated, and optimized by the HOMER software for the site of Ain Beni Mathar, located in eastern Morocco. Furthermore, the potential CO₂ emissions reduction from the different scenarios was estimated as well. The results show that the scenario including PVs and batteries is most cost-effective due to favorable climatic conditions and low costs. In fact, the most optimal HRES from a technical and economic standpoint is composed of a 48.8 kW PV plant, 213 batteries, a converter capacity of 43.8 kW, and an annual production of 117.5 MWh with only 8.8% excess energy, leading to an LCOE of 0.184 USD/kWh with a CO₂ emissions reduction of 81.7 tons per year, whereas scenarios with wind turbines, CSP, and biomass exhibit a higher LCOE in the range of 0.472–1.15 USD/kWh. This study’s findings confirm the technical and economic viability of HRESs to supply 100% of the electricity demand for rural Moroccan communities, through a proper HRES design. Full article

The advancement of efficient energy conversion and storage technologies is fundamentally linked to the development of electrochemical systems, including fuel cells, batteries, and electrolyzers, whose performance depends on key electrocatalytic reactions: hydrogen evolution (HER), oxygen evolution (OER), oxygen reduction (ORR), carbon dioxide reduction (CO₂RR), and nitrogen reduction (NRR). Beyond catalyst design, the electrolyte microenvironment significantly influences these reactions by modulating charge transfer, intermediate stabilization, and mass transport, making electrolyte engineering a powerful tool for enhancing performance. This review provides a comprehensive analysis of how fundamental electrolyte properties, including pH, ionic strength, ion identity, and solvent structure, affect the mechanisms and kinetics of these five reactions. We examine in detail how the electrolyte composition and individual ion contributions impact reaction pathways, catalytic activity, and product selectivity. For HER and OER, we discuss the interplay between acidic and alkaline environments, the effects of specific ions, interfacial electric fields, and catalyst stability. In ORR, we highlight pH-dependent activity, selectivity, and the roles of cations and anions in steering 2e⁻ versus 4e⁻ pathways. The CO₂RR and NRR sections explore how the electrolyte composition, local pH, buffering capacity, and proton sources influence activity and the product distribution. We also address challenges in electrolyte optimization, such as managing competing reactions and maximizing Faradaic efficiency. By comparing the electrolyte’s effects across these reactions, this review identifies general trends and design guidelines for enhancing electrocatalytic performance and outlines key open questions and future research directions relevant to practical energy technologies. Full article

All-solid-state lithium batteries (ASSLBs) are emerging as a promising alternative to conventional lithium-ion batteries, offering solutions to challenges related to energy density and safety. Their core advancement relies on breakthroughs in solid-state electrolytes (SEs). SEs can be broadly grouped into two main types: inorganic solid electrolytes (ISEs) and organic solid electrolytes (OSEs). ISEs offer high ionic conductivity (0.1~1 mS cm⁻¹), a lithium-ion transference number close to 1, and excellent thermal stability, but their intrinsic brittleness leads to poor interfacial wettability and processing difficulties, limiting practical applications. In contrast, OSEs exhibit good flexibility and interfacial compatibility but suffer from poor ionic conductivity (10⁻⁴~10⁻² mS cm⁻¹) due to high crystallinity at room temperature, in addition to poor thermal stability and weak mechanical integrity, making it difficult to match high-voltage cathodes and suppress lithium dendrite growth. Against this backdrop, the stability of the organic–inorganic interface plays a crucial role. However, challenges such as low overall conductivity and unstable interfaces still limit their performance. This review provides a microscopic perspective on lithium-ion transport pathways across the polymer phase, the inorganic filler phase, and their interfacial regions. It categorizes inert fillers and active fillers, analyzing their structure–performance relationships and emphasizing the synergistic effects of filler dimensionality, surface chemistry, and interfacial interactions. In addition, cutting-edge analytical methods such as time-of-flight secondary ion mass spectrometry (TOF-SIMS) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) have also been employed and are summarized into their roles for revealing the microstructures and dynamic interfacial behaviors of OICSEs. Finally, future directions are proposed, such as hierarchical pore structure design, surface functionalization, and simulation-guided optimization, aiming to provide theoretical insights and technological strategies for the development of high-performance composite electrolytes for ASSLBs. Full article

This study focuses on the power systems of inland waterway vessels in Chinese Yangtze River, systematically outlining the low-carbon technology pathways for different power system types. A comparative analysis is conducted on the technical feasibility, emission reduction potential, and economic viability of LNG, methanol, ammonia, pure electric and hybrid power systems, revealing the bottlenecks hindering the large-scale application of each system. Key findings indicate that: (1) LNG and methanol fuels offer significant short-term emission reductions in internal combustion engine power systems, yet face constraints from methane slip and insufficient green methanol production capacity, respectively; (2) ammonia enables zero-carbon operations but requires breakthroughs in combustion stability and synergistic control of NO_X; (3) electric vessels show high decarbonization potential, but battery energy density limits their range, while PEMFC lifespan constraints and SOFC thermal management deficiencies impede commercialization; (4) hybrid/range-extended power systems, with superior energy efficiency and lower retrofitting costs, serve as transitional solutions for existing vessels, though challenged by inadequate energy management strategies and multi-equipment communication protocol interoperability. A phased transition pathway is proposed: LNG/methanol engines and hybrid systems dominate during 2025–2030; ammonia-powered systems and solid-state batteries scale during 2030–2035; post-2035 operations achieve zero-carbon shipping via green hydrogen/ammonia. Full article

As China advances toward its 2060 carbon neutrality goal, the electrification of inland waterway shipping has emerged as a strategic pathway for reducing emissions. This study constructs a 2025–2060 dynamic material flow analysis framework that integrates three core dimensions: (1) all-electric ships (AES) diffusion, estimated via a GDP-elasticity model and carbon emission accounting; (2) battery technology evolution, including lithium iron phosphate and solid-state batteries; and (3) recycling system improvements, incorporating direct recycling, cascade utilization, and metallurgical processes. The research sets up three AES penetration scenarios, two battery technologies, and three recycling technology improvement scenarios, resulting in seven combination scenarios for analysis. Through multi-scenario simulations, it reveals synergistic pathways for resource security and decarbonization goals. Key findings include that to meet carbon reduction targets, AES penetration in inland shipping must reach 25.36% by 2060, corresponding to cumulative new ship constructions of 51.5–79.9k units, with total lithium demand ranging from 49.1–95.9 kt, and recycling potential reaching 5.4–25.2 kt. Results also reveal that under current allocation assumptions, the AES sector may face lithium shortages between 2047 and 2057 unless recycling rates improve or electrification pathways are optimized. The work innovatively links battery tech dynamics and recycling optimization for China’s inland shipping and provides actionable guidance for balancing decarbonization and lithium resource security. Full article

High-performance batteries for military and extreme environment applications require alternatives to conventional liquid lithium-ion batteries (LIBs), which suffer from poor low-temperature performance and safety risks. All-solid-state lithium batteries (ASSLBs) offer enhanced safety and superior low-temperature capability. In this work, we designed and fabricated composite solid-state electrolytes using polyvinylidene fluoride (PVDF) and polyacrylic acid (PAA) as polymer matrices, N,N-dimethylformamide (DMF) as the solvent, and lithium bis(trifluoromethane sulfonimide) (LiTFSI) as the lithium salt. Composite solutions with varying PAA mass ratios were prepared. Advanced three-dimensional (3D) printing technology enabled the rapid and precise fabrication of electrolyte membranes. An ionic conductivity of about 2.71 × 10⁻⁴ S cm⁻¹ at 25 °C, high mechanical strength, and good thermal properties can be achieved through component and 3D printing process optimization. Assembled LiCoO₂||PVDF@PAA||Li ASSLBs delivered an initial discharge capacity of 165.3 mAh/g at 0.1 mA cm⁻² (room temperature), maintaining 98% capacity retention after 300 cycles. At 0 °C, these cells provided 157.4 mAh/g initial capacity with 85% retention over 100 cycles at 0.1 mA cm⁻². This work identifies the optimal PAA ratio for enhanced electrochemical performance and demonstrates the viability of 3D printing for advanced ASSLB manufacturing. Full article

The modernization of agriculture can help humanity address major challenges such as population growth, climate change, and labor shortages. Semi-autonomous agricultural robots offer clear advantages in automating tasks and improving efficiency. However, in open-field conditions, their autonomy is limited by the size and weight of onboard batteries. Wireless charging is a promising solution to overcome this limitation. This work proposes a methodology for the design, modeling, and experimental validation of a wireless power transfer (WPT) system for battery recharging of agricultural robots. A brief review of WPT technologies is provided, followed by key design considerations, co-simulation, and testing results. The proposed WPT system uses a resonant inductive power transfer topology with series–series (SS) compensation, a high-frequency inverter (85 kHz), and optimized spiral planar coils, enabling medium-range operation under agricultural conditions. The main contribution lies in the first experimental assessment of WPT performance under real agricultural environmental factors such as soil moisture and water presence, combined with electromagnetic safety evaluation and robust component selection for harsh conditions. Results highlight both the potential and limitations of this approach, demonstrating its feasibility and paving the way for future integration with intelligent alignment and adaptive control strategies. Full article

As the demand for second-life lithium-ion battery applications continues to grow, efficient cell equalization has become essential to mitigate parameter inconsistencies and extend system longevity. Owing to their diverse origins and varying aging paths, second-life batteries exhibit significant parameter dispersion, which poses distinct challenges. In light of these issues, this paper presents a comprehensive review of passive, active, and dynamic equalization technologies. It analyzes the circuit topologies and control strategies associated with each method, with a particular focus on their applicability to second-life battery systems. Furthermore, emerging trends toward intelligent, modular, and adaptive equalization are discussed. Full article

Battery electric vehicles (BEVs) are gaining market share, yet range anxiety and sparse charging still create demand for hybrids with combustion-engine range extenders. Range-extender vehicles face high customer expectations for noise, vibration, and harshness (NVH) due to their direct comparability with fully electric vehicles. Key challenges include the vibrations of the internal combustion engine, especially from vehicle-induced starts, and the discontinuous operating principle. A technological concept to reduce vibrations in the drivetrain and on the engine mounts, called “FEVcom,” relies on rolling moment compensation. In this concept, a counter-rotating electric machine is coupled to the internal combustion engine via a gear stage to minimize external mount forces. However, due to high speed fluctuations of the crankshaft, the gear drive tends to rattle, which is perceived as disturbing and must be avoided. As part of this work, the rolling moment compensation system was examined regarding its vibration excitation, and an extension to prevent gear rattling was simulated and optimized. For the simulation, the extension, based on a chain or belt drive, was set up as a multi-body simulation model in combination with the range extender and examined dynamically at different speeds. Variations of the extended system were simulated, and recommendations for an optimized layout were derived. This work demonstrates the feasibility of successful rattling avoidance in a range-extender drivetrain with full utilization of the rolling moment compensation. It also provides a solid foundation for further detailed investigations and for developing a prototype for experimental validation based on the understanding gained of the system. Full article

Nanocomposites, which combine various nanomaterials, offer immense potential in the design of advanced materials for energy-related applications. These materials, engineered at the nanoscale, exhibit enhanced properties compared to their bulk counterparts, such as improved electrical conductivity, mechanical strength, and thermal stability. Nanocomposites have emerged as promising candidates for use in energy storage systems, including batteries and supercapacitors, by improving energy density, cycle life, and charge–discharge rates. In renewable energy technologies such as fuel cells, nanocomposites play a crucial role in enhancing efficiency and stability, which are vital for reducing costs and promoting the adoption of clean energy solutions. The unique properties of nanocomposites, such as high surface area and tunable composition, allow for the integration of multiple functionalities, making them ideal for multifunctional catalysts in energy conversion and environmental remediation. Additionally, nanocomposites enable the development of energy harvesting systems with improved performance and durability. These materials can be tailored by adjusting the composition of the nanomaterials, opening new opportunities for energy applications. The increasing research into nanocomposites continues to drive innovation in energy-related technologies, positioning them as a key enabler for sustainable energy solutions and future advancements in renewable energy systems. Full article

With the continuous development and innovation of thermal management technology for lithium-ion batteries, the advantages of direct immersion liquid cooling technology have become increasingly prominent. However, at present, there is relatively little research on immersion liquid cooling systems, and current research is still mainly focused on small-capacity battery systems. Therefore, taking a large-capacity battery pack as the research object, a new type of single-phase immersion liquid cooling system was designed. The battery pack has a charge and discharge rate of 1C, consists of 52 cells, and has a total capacity of 52.249 kWh. It was compared with traditional liquid cooling and static immersion liquid cooling. Then, the effects of the aperture of the flow distributor, the inlet flow rate of the cooling liquid, and the type of cooling liquid on the cooling performance of the dynamic immersion battery pack were discussed. The holes on the flow distribution plate are primarily designed to facilitate a relatively uniform distribution of incoming liquid flow. Our research found that compared with traditional liquid cooling and static immersion liquid cooling, the overall cooling performance of the dynamic immersion cooling system was significantly improved, with the maximum temperature T_max decreasing by 7.8 °C and 6.6 °C, the maximum temperature difference ΔT_max of the entire pack decreasing by 5.5 °C and 5.8 °C, and the maximum temperature difference U-DΔT_max between the top and bottom surfaces of the battery pack decreasing by 10.1 °C and 8.96 °C. An appropriate aperture had a positive impact on the cooling effect of the battery pack, with the best effect at a aperture of 4 mm. T_max and ΔT_max gradually decreased with an increase in the flow rate of the cooling liquid, with T_max decreasing from 42.3 °C to 31 °C and ΔT_max decreasing from 14.8 °C to 7.9 °C, but the rate of the temperature decrease gradually decreased. Deionized water in the cooling liquid had the best cooling effect, while ethyl silicone oil had the worst cooling effect. The novel single-phase immersion cooling system developed in this study serves as a valuable reference for the design of immersion liquid cooling systems in large-capacity battery packs, contributing to enhanced temperature uniformity and improved system safety. Full article

Batteries are ubiquitous, with their presence ranging from electric vehicles to portable electronics. Research focused on increasing average voltage, improving stability, and extending cycle longevity of batteries is pivotal for the advancement of battery technology. These advancements can be accelerated through research into battery chemistries. The traditional approach, which examines each material combination individually, poses significant challenges in terms of resources and financial investment. Physics-based simulations, while detailed, are both time-consuming and resource-intensive. Researchers aim to mitigate these concerns by employing Machine Learning (ML) techniques. In this study, we propose a Transformer-based deep learning model for predicting the average voltage of battery electrodes. Transformers, known for their ability to capture complex dependencies and relationships, are adapted here for tabular data and regression tasks. The model was trained on data from the Materials Project database. The results demonstrated strong predictive performance, with lower mean absolute error (MAE) and mean squared error (MSE), and higher R² values, indicating high accuracy in voltage prediction. Additionally, we conducted detailed per-ion performance analysis across ten working ions and apply sample-wise loss weighting to address data imbalance, significantly improving accuracy on rare-ion systems (e.g., Rb and Y) while preserving overall performance. Furthermore, we performed SHAP-based feature attribution to interpret model predictions, revealing that gravimetric energy and capacity dominate prediction influence, with architecture-specific differences in learned feature importance. This work highlights the potential of Transformer architectures in accelerating the discovery of advanced materials for sustainable energy storage. Full article

Conductive polymer thin films have emerged as a versatile class of materials with immense potential in energy storage and conversion technologies due to their unique combination of electrical conductivity, mechanical flexibility, and tunable physicochemical properties. This review comprehensively explores the role of conductive polymer thin films in three critical energy applications: supercapacitors, batteries, and solar cells. The paper examines key polymers such as polyaniline (PANI), polypyrrole (PPy), and poly(3,4-ethylenedioxythiophene) (PEDOT), focusing on their synthesis techniques, structural modifications, and integration strategies to enhance device performance. Recent advances in film fabrication methods, including solution processing, electrochemical deposition, and layer-by-layer assembly, are discussed with regard to achieving optimized morphology, conductivity, and electrochemical stability. Furthermore, the review highlights current challenges such as scalability, long-term durability, and interfacial compatibility, while outlining future directions for the development of high-performance, sustainable energy systems based on conductive polymer thin films. Full article

Hand gesture recognition is used in human–computer interaction, with multiple applications in assistive technologies, virtual reality, and smart systems. While vision-based methods are commonly employed, they are often computationally intensive, sensitive to environmental conditions, and raise privacy concerns. This work proposes a hardware/software co-optimized system for real-time hand gesture recognition using accelerometer data, designed for a portable, low-cost platform. A Convolutional Neural Network from TinyML is implemented on a Xilinx Zynq-7000 SoC-FPGA, utilizing fixed-point arithmetic to minimize computational complexity while maintaining classification accuracy. Additionally, combined architectural optimizations, including pipelining and loop unrolling, are applied to enhance processing efficiency. The final system achieves a 62× speedup over an unoptimized floating-point implementation while reducing power consumption, making it suitable for embedded and battery-powered applications. Full article