Search Results (2,037)

With the widespread use of lithium-ion batteries in electric vehicles, energy storage systems, and portable electronic devices, concerns regarding their thermal runaway have escalated, raising significant safety issues. Despite advances in existing thermal management technologies, challenges remain in addressing the complexity and variability of battery thermal runaway. These challenges include the limited heat dissipation capability of passive thermal management, the high energy consumption of active thermal management, and the ongoing optimization of material improvement methods. This paper systematically examines the mechanisms through which three main triggers—mechanical abuse, thermal abuse, and electrical abuse—affect the thermal runaway of lithium-ion batteries. It also reviews the advantages and limitations of passive and active thermal management techniques, battery management systems, and material improvement strategies for enhancing the thermal stability of batteries. Additionally, a comparison of the principles, characteristics, and innovative examples of various thermal management technologies is provided in tabular form. The study aims to offer a theoretical foundation and practical guidance for optimizing lithium-ion battery thermal management technologies, thereby promoting their development for high-safety and high-reliability applications. Full article

The literature clearly indicates that both academia and industry are strongly committed to developing comprehensive processes for spent Li-ion battery (LIB) recycling. In this regard, the current study presents an original contribution by providing a quantitative assessment of a large-scale recycling plant designed for the treatment of completely spent LIBs. In addition to a concept of the basic process, this assessment also considers a case study of a thermal integration and CO₂ capture subsystem. Process flow modeling software was used to evaluate the contribution of all process steps and equipment to overall energy consumption and to mass balance the data required for the technical assessment of the large-scale recycling plant. To underline the advantages and identify the optimal novel process concept, several key performance indicators were determined, such as recovery efficiency, specific energy/material consumption, and specific CO₂ emissions. In addition, the economic potential of the recycling plants was evaluated for the defined case studies based on capital and O&M costs. The results indicate that, even with CO₂ capture applied, the thermally integrated process with the combustion of hydrogen produced in the recycling plant remains the most promising large-scale configuration for spent LIB recycling. Full article

Accurate State of Charge (SOC) estimation for retired power batteries remains a critical challenge due to their degraded electrochemical properties and heterogeneous aging mechanisms. Traditional methods relying solely on electrical parameters (e.g., voltage and current) exhibit significant errors, as aged batteries experience altered internal resistance, capacity fade, and uneven heat generation, which distort the relationship between electrical signals and actual SOC. To address these limitations, this study proposes a surface temperature-assisted SOC estimation method, leveraging the distinct thermal characteristics of retired batteries. By employing infrared thermal imaging, key temperature feature regions—the positive/negative tabs and central area—are identified, which exhibit strong correlations with SOC dynamics under varying operational conditions. A Gated Recurrent Unit (GRU) neural network is developed to integrate multi-region temperature data with electrical parameters, capturing spatial–temporal thermal–electrical interactions unique to retired batteries. The model is trained and validated using experimental data collected under constant current discharge conditions, demonstrating superior accuracy compared to conventional methods. Specifically, our method achieves 64.3–68.1% lower RMSE than traditional electrical-parameter-only approaches (V-I inputs) across 0.5 C–2 C discharge rates. Results show that the proposed method reduces SOC estimation errors compared to traditional voltage-based models, achieving RMSE values below 1.04 across all tested rates. This improvement stems from the model’s ability to decode localized heating patterns and their hysteresis effects, which are particularly pronounced in aged batteries. The method’s robustness under high-rate operations highlights its potential for enhancing the reliability of retired battery management systems in secondary applications such as energy storage. Full article

The thermophysical behavior of solids (such as oxide compounds, for example) is crucial in applied physics and engineering, with particular regard to heterogeneous catalysis, sensors, high-temperature superconductors, and solid-state batteries. Research in geometric nonlinear theory has provided insights into crystal symmetry and phase compatibility under thermal and elastic stress. High-temperature stress significantly affects phase stability, making an understanding of solid thermodynamics essential for material performance. This study focuses on the mechanical and thermal interactions in solids, analyzing variations in mechanical stress and strain under extreme conditions. We propose a theoretical approach for a thermophysical model that, based on the study of the properties of the global thermal behavior of solids, can describe the thermodynamic effects of elastic deformations. Elastomers are used as a case study to validate the proposed approach. Full article

Amidst the background of accelerated global energy transition, the safety risk of lithium-ion battery energy storage systems, especially the fire hazard, has become a key bottleneck hindering their large-scale application, and there is an urgent need to build a systematic prevention and control program. This paper focuses on the fire characteristics and thermal runaway mechanism of lithium-ion battery energy storage power stations, analyzing the current situation of their risk prevention and control technology across the dimensions of monitoring and early warning technology, thermal management technology, and fire protection technology, and comparing and analyzing the characteristics of each technology from multiple angles. Building on this analysis, this paper summarizes the limitations of the existing technologies and puts forward prospective development paths, including the development of multi-parameter coupled monitoring and warning technology, integrated and intelligent thermal management technology, clean and efficient extinguishing agents, and dynamic fire suppression strategies, aiming to provide solid theoretical support and technical guidance for the precise risk prevention and control of lithium-ion battery storage power stations. 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

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

This study investigates a novel heat pipe integrated cooling system designed for thermal management of Tesla’s 4680 cylindrical lithium–ion batteries in electric vehicles (EVs). Through a comprehensive approach combining experimental analysis, 1-D AMESim simulations, and 3-D Computational Fluid Dynamics (CFD) modeling, the thermal performance of various wick structures and working fluid filling ratios was evaluated. The experimental setup utilized a triangular prism chamber housing three surrogate heater blocks to replicate the heat generation of 4680 cells under 1C, 2C, and 3C discharge rates. Results demonstrated that a blended fabric wick with a crown-shaped design (Wick 5) at a 30–40% filling ratio achieved the lowest maximum temperature (T_max of 47.0°C), minimal surface temperature deviation (ΔT_surface of 2.8°C), and optimal thermal resistance (R_th of 0.27°C/W) under 85 W heat input. CFD simulations validated experimental findings, confirming stable evaporation–condensation circulation at a 40% filling ratio, while identifying thermal limits at high heat loads (155 W). The proposed hybrid battery thermal management system (BTMS) offers significant potential for enhancing the performance and safety of high-energy density EV batteries. This research provides a foundation for optimizing thermal management in next-generation electric vehicles. Full article

Internal fins are commonly utilized as a passive technique to enhance natural convection, but their efficiency depends on complex interplay between fin design, material properties, and convective strength. This study presents an extensive numerical analysis of buoyancy-driven flow in square cavities containing a single horizontal fin on the hot wall. Over 9000 simulations were conducted, methodically varying the Rayleigh number (Ra = 10 to 10⁵), Prandtl number (Pr = 0.1 to 10), and fin characteristics, such as length, vertical position, thickness, and the thermal conductivity ratio (up to 1000), to assess their overall impact on thermal efficiency. Thermal enhancements compared to scenarios without fins are quantified using local and average Nusselt numbers, as well as a Nusselt number ratio (NNR). The results reveal that, contrary to conventional beliefs, long fins positioned centrally can actually decrease heat transfer by up to 11.8% at high Ra and Pr due to the disruption of thermal plumes and diminished circulation. Conversely, shorter fins located near the cavity’s top and bottom wall edges can enhance the Nusselt numbers for the hot wall by up to 8.4%, thereby positively affecting the development of thermal boundary layers. A U-shaped Nusselt number distribution related to fin placement appears at Ra ≥ 10³, where edge-aligned fins consistently outperform those positioned mid-height. The benefits of high-conductivity fins become increasingly nonlinear at larger Ra, with advantages limited to designs that minimally disrupt core convective patterns. These findings challenge established notions regarding passive thermal enhancement and provide a predictive thermogeometric framework for designing enclosures. The results can be directly applied to passive cooling systems in electronics, battery packs, solar thermal collectors, and energy-efficient buildings, where optimizing heat transfer is vital without employing active control methods. Full article

Electric buses (EBs) are increasingly adopted for their environmental and operational benefits, yet their real-world efficiency is influenced by climate, route characteristics, and auxiliary energy demands. While most existing research identifies winter as the most energy-intensive season due to cabin heating and reduced battery performance, this study presents a contrasting perspective based on a three-year longitudinal analysis of the LYMMO fleet in Orlando, Florida—a subtropical U.S. region. The findings reveal that summer is the most energy-intensive season, primarily due to sustained HVAC usage driven by high ambient temperatures—a seasonal pattern rarely reported in the current literature and a key regional contribution. Additionally, idling time exceeds driving time across all seasons, with HVAC usage during idling emerging as the dominant contributor to total energy consumption. To mitigate these inefficiencies, a proxy-based HVAC energy estimation method and an optimization model were developed, incorporating ambient temperature and peak passenger load. This approach achieved up to 24% energy savings without compromising thermal comfort. Results validated through non-parametric statistical testing support operational strategies such as idling reduction, HVAC control, and seasonally adaptive scheduling, offering practical pathways to improve EB efficiency in warm-weather transit systems. 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

In the context of urban decarbonization, multi-energy microgrids (MEMGs) are gaining increasing relevance due to their ability to enhance synergies across multiple energy vectors. This study presents a block-based MILP framework developed to optimize the operations of a real MEMG, with a particular focus on accurately modeling the structure of electricity and natural gas bills. The objective is to assess the added economic value of integrating a battery energy storage system (BESS) under the assumption it is employed to provide implicit flexibility—namely, bill management, energy arbitrage, and peak shaving. Results show that under assumed market conditions, tariff schemes, and BESS costs, none of the analyzed BESS configurations achieve a positive net present value. However, a 2 MW/4 MWh BESS yields a 3.8% reduction in annual operating costs compared to the base case without storage, driven by increased self-consumption (+2.8%), reduced thermal energy waste (–6.4%), and a substantial decrease in power-based electricity charges (–77.9%). The performed sensitivity analyses indicate that even with a significantly higher day-ahead market price spread, the BESS is not sufficiently incentivized to perform pure energy arbitrage and that the effectiveness of a time-of-use power-based tariff depends not only on the level of price differentiation but also on the BESS size. Overall, this study provides insights into the role of BESS in MEMGs and highlights the need for electricity bill designs that better reward the provision of implicit flexibility by storage systems. Full article

Electrochromic devices (ECDs) capable of modulating both visible color and infrared (IR) emissivity are promising for applications in smart thermal camouflage and multifunctional displays. However, conventional transmissive ECDs suffer from limited IR modulation due to the low IR transmittance of transparent electrodes. Here, we report a reflection-type electrochromic zinc-ion battery (HWEC-ZIB) using a self-doped polyaniline nanorod film (SP(ANI-MA)) as the active layer. By positioning the active material at the device surface, this structure avoids interference from transparent electrodes and enables broadband and efficient IR emissivity tuning. To prevent electrolyte-induced IR absorption, a thermal lamination encapsulation method is employed. The optimized device achieves emissivity modulation ranges of 0.28 (3–5 μm) and 0.19 (8–14 μm), delivering excellent thermal camouflage performance. It also exhibits a visible color change from earthy yellow to deep green, suitable for various natural environments. In addition, the HWEC-ZIB shows a high areal capacity of 72.15 mAh cm⁻² at 0.1 mA cm⁻² and maintains 80% capacity after 5000 cycles, demonstrating outstanding electrochemical stability. This work offers a versatile device platform integrating IR stealth, visual camouflage, and energy storage, providing a promising solution for next-generation adaptive camouflage and defense-oriented electronics. Full article

The reliability of unmanned aerial vehicle (UAV) energy storage battery systems is critical for ensuring their safe operation and efficient mission execution, and has the potential to significantly advance applications in logistics, monitoring, and emergency response. This paper reviews theoretical and technical advancements in UAV battery reliability, covering definitions and metrics, modeling approaches, state estimation, fault diagnosis, and battery management system (BMS) technologies. Based on international standards, reliability encompasses performance stability, environmental adaptability, and safety redundancy, encompassing metrics such as the capacity retention rate, mean time between failures (MTBF), and thermal runaway warning time. Modeling methods for reliability include mathematical, data-driven, and hybrid models, which are evaluated for accuracy and efficiency under dynamic conditions. State estimation focuses on five key battery parameters and compares neural network, regression, and optimization algorithms in complex flight scenarios. Fault diagnosis involves feature extraction, time-series modeling, and probabilistic inference, with multimodal fusion strategies being proposed for faults like overcharge and thermal runaway. BMS technologies include state monitoring, protection, and optimization, and balancing strategies and the potential of intelligent algorithms are being explored. Challenges in this field include non-unified standards, limited model generalization, and complexity in diagnosing concurrent faults. Future research should prioritize multi-physics-coupled modeling, AI-driven predictive techniques, and cybersecurity to enhance the reliability and intelligence of battery systems in order to support the sustainable development of unmanned systems. Full article

In recent years, Ga-based liquid metals have emerged as a prominent research focus in catalysis, owing to their unique properties, including fluidity, low melting point, high thermal and electrical conductivity, and tunable surface characteristics. This review summarizes the synthesis strategies for Ga-based liquid metal catalysts, with a focus on recent advances in their applications across electrocatalysis, thermal catalysis, photocatalysis, and related fields. In electrocatalysis, these catalysts exhibit potential for reactions such as electrocatalytic CO₂ reduction, electrocatalytic ammonia synthesis, electrocatalytic hydrogen production, and the electrocatalytic oxidation of alcohols. As to thermal catalysis, these catalysts are employed in processes such as alkane dehydrogenation, selective hydrogenation, thermocatalytic CO₂ reduction, thermocatalytic ammonia synthesis, and thermocatalytic plastic degradation. In photocatalysis, they can be used in other photocatalytic reactions such as organic matter degradation and overall water splitting. Furthermore, Ga-based liquid metal catalysts also exhibit distinct advantages in catalytic reactions within battery systems and mechano-driven catalysis, offering innovative concepts and technical pathways for developing novel catalytic systems. Finally, this review discusses the current challenges and future prospects in Ga-based liquid metal catalysis. Full article