Search Results (1,352)

Lithium-ion batteries are widely used in energy storage and power systems due to their high energy density, long cycle life, and stability. Accurate prediction of the state of health (SOH) of batteries is critical to ensuring their safe and reliable operation. However, the prediction task remains challenging due to various complex factors. This paper proposes a hybrid TCN–Transformer–BiLSTM prediction model for battery SOH estimation. The model is first validated using the NASA public dataset, followed by further verification with dynamic operating condition simulation experimental data. Health features correlated with SOH are identified through Pearson analysis, and comparisons are conducted with existing LSTM, GRU, and BiLSTM methods. Experimental results demonstrate that the proposed model achieves outstanding performance across multiple datasets, with root mean square error (RMSE) values consistently below 2% and even below 1% in specific cases. Furthermore, the model maintains high prediction accuracy even when trained with only 50% of the data. Full article

Traditional liquid electrolyte batteries face safety concerns such as leakage and flammability, while further optimization has reached a bottleneck. Solid electrolytes are therefore considered a promising solution. Here, a PEO–LiTFSI–LATP (PELT) composite electrolyte was developed by incorporating nanosized Li_1.3Al_0.3Ti_1.7(PO₄)₃ fillers into a polyethylene oxide matrix, effectively reducing crystallinity, enhancing mechanical robustness, and providing additional Li⁺ transport channels. The PELT electrolyte exhibited an electrochemical stability window of 4.9 V, an ionic conductivity of 1.2 × 10⁻⁴ S·cm⁻¹ at 60 °C, and a Li⁺ transference number (tLi+) of 0.46, supporting stable Li plating/stripping for over 600 h in symmetric batteries. More importantly, to address poor electrode–electrolyte contact in conventional layered cells, we proposed an integrated electrode–electrolyte architecture by in situ coating the PELT precursor directly onto LiFePO₄ cathodes. This design minimized interfacial impedance, improved ion transport, and enhanced electrochemical stability. The integrated PELT/LFP battery retained 74% of its capacity after 200 cycles at 1 A·g⁻¹ and showed superior rate capability compared with sandwich-type batteries. These results highlight that coupling LATP-enhanced polymer electrolytes with an integrated architecture is a promising pathway toward high-safety, high-performance solid-state lithium-ion batteries. Full article

In this work, a novel solid polymer electrolyte with a disordered structure has been designed, combining polyethylene glycol (PEG) as the flexible segments and hexamethylene diisocyanate (HDI) as the rigid segments. The synthesis was realized by alternating flexible PEG with rigid HDI through a peptide bond (–CO–NH–), which disrupts the ordered structures of PEG, generating electron-deficient Lewis acid groups. The pathbreaking introduction of HDI blocks not only bridges links between the PEG molecules but also generates electron-deficient Lewis acid groups. Therefore, the original ordered structures of PEG are disrupted by both the alternating chains between PEG and HDI and the Lewis acid groups. As a result, the PEG_H/L4000 electrolytes (PEG molecular weight of 4000) exhibit a strong anion-capture ability that decreases the crystallinity of polymers, which further achieves a high ionic conductivity close to 10⁻³ S·cm⁻¹ with the lithium-ion transference numbers up to 0.88. The symmetric Li|PEG_H/L4000|Li cells maintain a low and stable voltage polarization for more than 800 h at 0.1 mA·cm⁻². Furthermore, the LiFePO₄|PEG_H/L4000|Li all-solid-state cells perform well both in cycling and rate performances. The design of polymer disordered structures for polymer electrolytes provides a new thought for manufacturing all-solid-state lithium-ion batteries with high safety as well as long life. Full article

The electrochemical performance of Li-ion batteries employing LiFePO₄ (LFP) cathodes supported by bio-sourced activated carbon derived from millet cob (MC) and water hyacinth (WH) were systematically investigated. Carbon activation was carried out using potassium hydroxide (KOH) at varying mass ratios of KOH to precursor material: 1:1, 2:1, and 5:1 for both WH and MC-derived carbon. The physical properties (X-ray diffraction patterns, BET surface area, micropore and mesopore volume, conductivity, etc.) and electrochemical performance (specific capacity, discharge at various current rates, electrochemical impedance measurement, etc.) were determined. Material characterization revealed that the activated carbon derived from MC exhibits an amorphous structure, whereas that obtained from WH is predominantly crystalline. High specific surface areas were achieved with activated carbons synthesized using a low KOH-to-carbon mass ratio (1:1), reaching 413.03 m²·g⁻¹ for WH and 216.34 m²·g⁻¹ for MC. However, larger average pore diameters were observed at higher activation ratios (5:1), measuring 8.38 nm for KOH/WH and 5.28 nm for KOH/MC. For both biomass-derived carbons, optimal electrical conductivity was obtained at a 2:1 activation ratio, with values of 14.7 × 10⁻³ S·cm⁻¹ for KOH/WH and 8.42 × 10⁻³ S·cm⁻¹ for KOH/MC. The electrochemical performance of coin cells based on cathodes composed of 85% LiFePO₄, 8% of these activated carbons, and 7% polyvinylidene fluoride (PVDF) as a binder, with lithium metal as the anode were studied. The LiFePO₄/C (LFP/C) cathodes exhibited specific capacities of up to 160 mAh·g⁻¹ at a current rate of C/12 and 110 mAh·g⁻¹ at 5C. Both LFP/MC and LFP/WH cathodes exhibit optimal energy density at specific values of pore size, pore volume, charge transfer resistance (R_ct), and diffusion coefficient (D_Li), reflecting a favorable balance between ionic transport, accessible surface area, and charge conduction. Maximum energy densities relative to active mass were recorded at 544 mWh·g⁻¹ for LFP/MC 2:1, 554 mWh·g⁻¹ for LFP/WH 2:1, and 568 mWh·g⁻¹ for the reference LFP/graphite system. These performance results demonstrate that the development of high-performing bio-sourced activated carbon depends on the optimization of various parameters, including chemical composition, specific surface area, pore volume and size distribution, as well as electrical conductivity. Full article

The rapid growth of the electric vehicle (EV) market has highlighted the critical importance of securing a stable supply chain for lithium-ion battery (LIB) resources, thereby increasing the need for efficient recycling technologies. Among these, lithium recovery remains a major challenge due to significant losses during conventional processes. In this study, a chlorination roasting process was introduced to convert Li₂O in spent LIBs into LiCl, which was subsequently evaporated for selective lithium extraction and recovery. Roasting experiments were conducted under air, vacuum, and N₂ conditions at 800–1000 °C for 1–5 h, with Cl/Li molar ratios ranging from 0.5 to 8. The optimal condition for lithium evaporation, achieving 100% recovery, was identified as 1000 °C for 5 h, with a Cl/Li molar ratio of 6 under vacuum. Following lithium removal, residual valuable metals were extracted through H₂SO₄ leaching, and the effects of acid concentration and H₂O₂ addition on leaching efficiency were examined. The air-roasted samples exhibited the highest leaching performance, while the vacuum- and N₂-roasted samples showed relatively lower efficiency; however, the addition of H₂O₂ significantly enhanced leaching yields in these cases. Full article

In conventional lithium-ion batteries (LIBs), active lithium loss during solid electrolyte interphase (SEI) formation reduces coulombic efficiency and energy density. Cathode pre-lithiation can effectively compensate for this irreversible lithium consumption. To address limitations of conventional pre-lithiation agents—such as complex synthesis and air instability—a Ketjen black-coated lithium oxalate nanocomposite (Li₂C₂O₄@KB) using high-energy ball milling and spray drying was developed. This composite leverages the advantages of Li₂C₂O₄, including a mild decomposition potential (4.26 V vs. Li⁺/Li), high theoretical lithium compensation capacity (525 mAh·g⁻¹), and environmentally benign decomposition products, and significantly improves electronic conductivity and reduces particle size. When incorporated in NCM622 full cells, the initial capacity is increased by 18.21 mAh·g⁻¹ at 0.3 C, with a 29.22% enhancement in capacity retention after 50 cycles at 0.3 C. At 1 C, the initial capacity is higher by 15.79 mAh·g⁻¹, accompanied with a 7.72% improvement in retention after 100 cycles. The Li₂C₂O₄@KB composite exhibits great promise as a practical and efficient cathode pre-lithiation additive for next-generation high-energy-density LIBs. Full article

Lithium-ion batteries (LIBs) are critical components in safety-critical systems such as electric vehicles, aerospace, and grid-scale energy storage. Their degradation over time can lead to catastrophic failures, including thermal runaway and uncontrolled combustion, posing severe threats to human safety and infrastructure. Developing a robust AI framework for degradation prognostics in safety-critical systems is essential to mitigate these risks and ensure operational safety. However, sensor noise, dynamic operating conditions, and the multi-scale nature of degradation processes complicate this task. Traditional denoising and modeling approaches often fail to preserve informative temporal features or capture both abrupt fluctuations and long-term trends simultaneously. To address these limitations, this paper proposes a hybrid data-driven framework that combines Sample Entropy-guided Variational Mode Decomposition (SE-VMD) with K-means clustering for adaptive signal preprocessing. The SE-VMD algorithm automatically determines the optimal number of decomposition modes, while K-means separates high- and low-frequency components, enabling robust feature extraction. A dual-branch architecture is designed, where Gated Recurrent Units (GRUs) extract short-term dynamics from high-frequency signals, and Transformers model long-term trends from low-frequency signals. This dual-branch approach ensures comprehensive multi-scale degradation feature learning. Additionally, experiments with varying sliding window sizes are conducted to optimize temporal modeling and enhance the framework’s robustness and generalization. Benchmark dataset evaluations demonstrate that the proposed method outperforms traditional approaches in prediction accuracy and stability under diverse conditions. The framework directly contributes to Artificial Intelligence for Security by providing a reliable solution for battery health monitoring in safety-critical applications, enabling early risk mitigation and ensuring operational safety in real-world scenarios. Full article

The concept behind this undertaking was to create environmentally friendly and sustainable air-conditioning systems supported by energy storage units, as well as to conduct comparative calculations of investment and operational costs to assess their economic viability. In order to meet sustainability requirements, detailed analysis was followed by a decision to utilise cold storage units in which energy is stored through the phase change of water into ice. Aiming to achieve high efficiency, strong reliability and enhanced operational dynamics, a multi-circuit model for coolant flow was developed, incorporating a variable-speed compressor drive. High functionality and performance were attained through the introduction of container vibrations, which resulted in the formation of ice slurry particles in spherical containers placed within an aqueous glycol solution serving as the heat exchange medium. The concept of this technology, along with its accompanying mathematical models, was validated, and the results of this work are presented in the article. To evaluate the competitiveness of air-conditioning systems, the developed solution based on cold storage technology is compared with a lithium-ion battery system and a conventional configuration powered directly by the grid. The results demonstrate that the cold-storage-based air-conditioning system outperforms both reference systems in terms of energy efficiency. An analysis of the full operational cycle indicates that the proposed solution consumes significantly less energy than systems using lithium-ion battery storage. The investment costs are almost twenty percent lower, while service, maintenance and disposal expenses are negligible. These attributes make it a competitive solution that is both economically and environmentally sustainable. In summary, the proposed technology fully satisfies the key principles of sustainability. It does not deplete natural resources, minimises the environmental impact, offers long-term reliability and contributes to lower energy bills and more responsible resource use. Full article

The intrinsic instability of organic electrolytes seriously impedes practical applications of lithium–oxygen (Li-O₂) batteries. Recent studies have shown that the use of high-concentration electrolytes can suppress the decomposition reaction of electrolytes and help enhance cell reversibility. However, the fundamental nature of concentrated electrolytes’ ability to improve the chemical durability and stability of Li-O₂ batteries remains unclear. In this work, we conducted computational studies to elucidate the origin of the enhanced oxidative/reductive stability of three representative solvents—DMSO, DME, and EC—in high-concentration electrolytes. The modeling results identify that Li⁺-solvent complexes, one of the solvate components, are the easiest to decompose in concentrated electrolytes. Thermodynamic and kinetic characterizations reveal that more anions in concentrated electrolytes are responsible for improving the oxidative and reductive stability of electrolytes. In addition, more Li⁺ ions, acting as a scavenging or stabilizing agent for superoxide anion (O₂⁻), also improve the stability of electrolytes against oxidation in Li-O₂ batteries. This work provides a mechanistic understanding of the enhanced cycle stability of a Li-O₂ battery using high-concentration electrolytes. Full article

A novel architectural design is proposed to optimize the thermal management of lithium-ion batteries (LiBs) through a software-enabled switching mechanism. This approach addresses critical challenges such as hot-spot generation, peak temperature rise, and uneven thermal distribution—issues commonly observed in conventional single-terminal battery modules (STBMs). The proposed dual-terminal configuration integrates an enhanced battery pack structure with a software-enabled switching algorithm that identifies the 50% depth of discharge (DoD) and toggles the current path between two terminals to supply the load. Correspondingly, the module also incorporates the division of four thermal zones and four regions concept in the battery module (BM). Experiments were conducted to evaluate the performance of the proposed model at five different C-rates: 0.5C, 0.75C, 1C, 1.25C, and 1.5C. The results demonstrate that the software-enabled dual-terminal switching (Se-DTS) consistently outperforms the STBM across three key aspects. First, in terms of peak temperature, Se-DTS achieved reductions of 19.33%, 17.83%, and 12.72% at C-rates of 1C, 1.25C, and 1.5C, respectively. Second, in thermal distribution, Se-DTS improved performance, with an 86.1% reduction at 1.25C. Third, regarding hot-spot reduction, improvements of 100% (regional level) and 72.22% (zonal level) were observed at 1.25C, while at 1.5C, an 80% improvement was achieved at the zonal level, without using a cooling system. Full article

Hydrogels have garnered significant attention as multifunctional materials in next-generation rechargeable batteries due to their high ionic conductivity, mechanical flexibility, and structural tunability. This review presents a comprehensive overview of hydrogel types—including natural, synthetic, composite, carbon-based, conductive polymer, and MOF hydrogels—and their synthesis methods, such as chemical crosslinking, self-assembly, and irradiation-based techniques. Characterization tools like SEM, XRD, and FTIR are discussed to evaluate their microstructure and performance. In rechargeable batteries systems, hydrogels enhance ionic transport and mechanical stability, particularly in lithium-ion, sodium-ion, zinc-ion, magnesium-ion, and aluminum-ion batteries. Despite their advantages, hydrogels face challenges such as limited mechanical strength, reduced stability under extreme conditions, and scalability issues. Current research focuses on advanced formulations, self-healing mechanisms, and sustainable materials to overcome these limitations. This review highlights the pivotal role of hydrogels in shaping the future of flexible, high-performance, and environmentally friendly secondary batteries. Full article

The increasing demand for high-efficiency cooling technologies necessitates improved methods to prevent degradation and ensure reliable operation of lithium–ion batteries. Conventional PCM (phase change material)-based cooling systems are limited by low thermal conductivity and uneven phase change processes, which lead to non-uniform thermal distribution and diminished performance. In response to these challenges, this study introduces a hybrid thermal management system that combines an indirect liquid-cooling structure with multiple cooling channel configurations within a PCM-based battery pack. Numerical simulations were conducted to systematically assess the thermal performance of the proposed design. Experimental validation with various cooling media showed that PCM achieved the greatest reduction in temperature (47%) and the longest isothermal duration (56 min) under air-cooled conditions, surpassing thermally conductive adhesive (40%) and silicone oil (26%) for temperature decrease. Vertical temperature differentials were effectively reduced, staying below only 2 °C for silicone oil and reaching a maximum of 4 °C for PCM. Phase change evaluation indicated that after 30 min of operation, only 37% of the PCM volume had melted, highlighting localized constraints in heat transfer. Comparative analysis among four liquid-cooling channel arrangements (A–D) and a standalone PCM system demonstrated that configuration D exhibited the highest cooling capability, lowering the battery surface temperature by as much as 9 °C (17.8%). Flow rate analysis determined that increases above 0.2 L/min resulted in only modest thermal improvements (<1 °C), with 0.108 L/min identified as the most efficient rate. Relative to PCM-only designs, the advanced hybrid cooling system achieved significantly enhanced thermal regulation and temperature uniformity, underscoring its promise as a superior solution for lithium–ion battery thermal management. Full article

This article analyses the possibility of using Li-ion batteries removed from battery electric vehicles (BEVs) as short-term energy storage devices in a near-zero energy building (nZEB) in conjunction with a rooftop photovoltaic (PV) system. The technical and economic feasibility of this solution was compared to that of a standard commercial LIB (Lithium-Ion battery) BESS Battery Energy Storage System). Two generations of the same BEV model battery were tested to analyse their suitability for powering a building. The necessary changes to the setup of such a battery for building power supply purposes were analysed, as well as its suitability. As a result, analyses of profitability over the predicted life span and NPV (net present value) of SLEVBs (second-life BEV batteries) for building power were carried out. The study also conducted preliminary research on the effectiveness of such projects and their pros and cons in terms of security. The author calculates the profitability of a ready-made PV BESS with a set of SLEVBs, estimating the payback periods for such investments relative to electricity prices in Poland. The article concludes on the potential of SLEVBs to support self-consumption in nZEB buildings and its environmental impact on the European circular economy. Full article

The potential of silicon carbide (SiC) as a promising high-capacity and stable anode material is hindered by poor electronic conductivity and slow lithium diffusion kinetics. Here, we report a one-step laser chemical vapor deposition (LCVD) process to directly synthesize porous graphene@SiC heterostructures on carbon fiber substrates. This in situ method yields an integral, binder-free electrode architecture that enhances mechanical robustness against pulverization. A critical feature of this heterostructure is the built-in electric field at the graphene–SiC interface, which is revealed by theoretical calculations to significantly accelerate charge transport and lithium-ion diffusion. The resulting anode delivers a high reversible capacity of 668 mAh·g⁻¹ after 100 cycles at 0.1 A·g⁻¹. More remarkably, a unique multi-stage activation mechanism is discovered, leading to an unprecedented capacity rebound to 735 mAh·g⁻¹ after cycling at rates up to 5 A·g⁻¹. This activation process is observed to accelerate with increasing current density in the 0.1–2 A·g⁻¹ range. Furthermore, post-cycling analysis via XRD, TEM, and XPS confirms both the structural durability of the electrode and a reversible lithium intercalation mechanism, providing a critical foundation for the future design of high-performance LIB anodes. Full article

This paper presents a practical experiment for estimating the state-of-charge (SOC) of individual cells in a series-connected heterogeneous lithium-ion battery pack, where only the terminal voltage of the battery pack is measured. To deal with real-time computation constraints, the dense extended Kalman filter (DEKF) algorithm has been proposed in the literature, which has a significantly lower computational complexity compared to the regular extended Kalman filter for this specific estimation problem. This work supplements the existing work by conducting a real-world experiment to validate the performance of the DEKF. Specifically, experiments involving a battery pack of three cells connected in series were conducted, where the battery pack was discharged under a constant current load. A genetic algorithm was applied to identify missing model parameters, as well as tuning the DEKF for optimal convergence and accurate SOC estimation. Our experimental results confirm that the proposed DEKF accurately estimates the SOC of each cell regardless of the hardware limitations and uncertainty, making it suitable for low-cost, real-time battery management systems. In particular, the SOC estimation error can be kept well under 1% even if the initial estimate is far from the true SOC. Full article