Search

Energy storage devices (ESD) which are intended to power electronic devices, used in close contact of human skin, are desirable to be safe and non-toxic. In light of this requirement, Zn based energy storage devices seem to provide a viable pathway as they mostly employ aqueous based electrolytes which are safe and non-toxic in their functioning. Additionally, having a flexible ESD will play a crucial role as it will enable the ESD to conform to the varying shapes and sizes of wearable electronics which they energize. In this work, we have developed an inkjet-printed Zinc ion battery (IPZIB) with planar electrode configuration over bond paper substrate. Zn has been used as the negative electrode, MnO2 is used as the positive electrode with Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) as the active binder. Conducting tracks of reduced graphene oxide (rGO) are used to construct the current collector on the paper substrate. The fabricated IPZIB delivered a high discharge capacity of 300.14 mAh g−1 at a current density of 200 mA g−1. The energy density of the IPZIB is observed as 330.15 Wh kg−1 at a power density of 220 W kg−1 and retains an energy density of 94.36 Wh kg−1 at a high power density of 1650 W kg−1. Finally, we have demonstrated the capability of the IPZIB to power a LED at various bending and folding conditions which indicates its potential to be used in the next generation flexible and wearable electronic devices. [ABSTRACT FROM AUTHOR]

Wearable electronic energy storage devices usually require the integration of flexible mechanisms and uncompromising electrochemistry of lithium-ion batteries (LIBs). Most of the studies in this field have mainly focused on enhancing the electrochemical properties of the material, while the significance of its flexibility and mechanical properties has been relatively ignored. In this study, the 20 wt % carbon fibers (CFs) composite N-doped flexible carbon nanofiber paper (NFCFP) was prepared through a facile PFI refiner and Bauer sieve of pulping and papermaking machinery sieve-assisted methods combined with annealing technology. The NFCFP-700 with high pyridine N content shows good ion transport and storage performance, the specific capacity remained 308 mAh⸱g−1 after 100 cycles at 0.1 C, and even at 1 C, the specific capacity of the electrode material instead increases constantly at 142 mAh⸱g−1. According to density functional theory (DFT) calculations, the coexistence of pyridine N content and defects in carbon materials was found to enhance the adsorption energy (E ad) of lithium, and the N4V2 locally show the most negative electrostatic potential (ESP) distribution, which was more favorable for the adsorption of Li+ being positively charged. This insight from DFT studies combined with experimental data emphasizes the favorable impact of pyridine N content and defects on the lithium adsorption process in carbon materials, also providing valuable information for the design and optimization of materials for lithium storage applications. [ABSTRACT FROM AUTHOR]

Cellulose is now considered as an appealing environment friendly material for the development of sustainable separators for rechargeable batteries. This study thus aims to develop high performance paper based ceramic separators with superior electrolyte wettability (>170 %), high thermal stability (>200 °C) and excellent flame safety. While developing paper based ceramic separator, extensive studies are carried out to understand thenature and functionality of different nano-structured ceramic materials (Al 2 O 3 , BaTiO 3 and ZrO 2) impregnated in paper matrix. Nano-ZrO 2 facilitates an effective pathway for Li +-ion transport (t Li + = 0.51), whereas BaTiO 3 and Al 2 O 3 ceramics show moderate Li +-ion transport properties (t Li+ of 0.29 and 0.30 respectively). Electrochemical Impedance Spectroscopy (EIS) measurement clearly reveals that ZrO 2 exhibits more interfacial compatibility with the electrodes (MCMB and LiNi 1/3 Mn 1/3 Co 1/3 O 2) compared to the other two ceramic separators during full cell operation. The developed paper separators show excellent electrochemical properties in terms of cycling (tested 300 cycles), multi-electrode compatibility and rate capabilities at different current densities of 0.1–1.2 mAcm−2. The pre- and post-electrochemical EIS data reveal that ZrO 2 based impregnation offers significantly lower charge transfer resistance compared to the other two separators. The study thus demonstrates a real promise for its successful application in Li-ion battery towards achieving sustainability and safety. [Display omitted] • Sustainable, flexible and high safety ceramic based paper separators for LIBs. • Separators were developed using easy to scale up wet-coating process. • Ceramic impregnation affects physical and electrochemical properties of the separators. • Paper separators show superior electrolyte wettability and high thermal stability. • Better electrochemical performances and flame safety are other important advantages. [ABSTRACT FROM AUTHOR]

The paper describes the digital twin of a Li-ion battery cell based on the MATLAB/Simulink generic model. The digital twin is based on measured data for constant current/constant voltage charging and discharging cycles with State of Health (SoH) up to 79%, also including fast charging. Mathematical equations used for the digital twin are obtained by 3D data fitting of measured SoH, battery capacity, and battery cell current. The input to the proposed digital twin is only the measured battery cell current, and its output includes State of Charge (SoC), SoH, and battery cell voltage. The designed digital twin is tested and compared with MATLAB/Simulink generic model and battery cell measurements for constant discharging current and dynamically generated discharging current profile. The results show significant improvement in the generic MATLAB/Simulink model. [ABSTRACT FROM AUTHOR]

Freestanding tin oxide-boron oxide/reduced graphene oxide (SnO2-B2O3/rGO) nanocomposite anode was produced for Li-ion cells. This binder-free flexible paper anode structure was fabricated by combining SnO2-B2O3 composite and graphene oxide which were synthesized through the sol–gel method and Hummers’ method, respectively. Field emission gun scanning electron microscopy, high-resolution transmission electron microscopy, energy dispersive X-ray spectrometer, Fourier transform infrared spectroscopy, Raman spectroscopy, and X-ray diffraction were utilized to characterize anode materials. The Williamson-Hall (W-H) analysis was applied using XRD data to determine crystal size and strain of the lattice. Electrochemical tests, cyclic voltammetry, and electrochemical impedance spectroscopy measurements were performed to determine electrochemical properties of the anodes. The results indicated that the anode formed with SnO2-B2O3 particles anchored on the rGO layers provided higher discharge capacity (838 mAhg-1) than that of SnO2/rGO (395 mAh g-1) after 100 cycles. The electron-deficient nature of boron supplied an effective increase in electrochemical energy storage performance. [ABSTRACT FROM AUTHOR]

Abstract A facile one-step solid-phase synthesis strategy is developed for synthesizing a binder-free molybdenum disulfide/carbon fibers paper (MoS 2 /CFP) anode. The microstructure, composition, morphology and electrochemical performances were investigated. It is found that the thin MoS 2 layers are well anchored on the interlaced carbon fibers to form MoS 2 /CFP, which has mesoporous structure and large specific surface area of ∼18.8 m2g-1. As a result, the obtained MoS 2 /CFP anode exhibits a reversible capacity of 261 mAh·g−1 with 31.2% loading ratio of MoS 2. After subtracting the capacity of CFP, the MoS 2 in the composite anode delivers a reversible capacity of 539 mAh·g−1 and shows better cycle stability than commercial MoS 2 after 100 cycles at 100 mA g−1. The remarkable electrochemical performances could be attributed to the buffer space among carbon fibers for the volume changes of MoS 2 as well as the highly conductive carbon fibers network, suggesting that the MoS 2 /CFP is a promising binder-free anode for lithium-ion batteries. Graphical abstract Image 1 Highlights • A one-step solid-phase synthesis strategy is developed to fabricate MoS 2 /CFP anode. • The MoS 2 and the carbon matrix of MoS 2 /CFP composite were synthesized synchronously. • The MoS 2 /CFP anode exhibits enhanced cycling performance and high-rate capability. • The mechanism of the enhanced electrochemical properties was discussed for MoS 2 /CFP. [ABSTRACT FROM AUTHOR]

MoO 3 -based anodes for lithium storage have attracted more attentions due to the relatively high specific capacity of 1117 mAh g–1 and good chemical stability. Compound MoO 3 with other functional materials and construction of unique micromorphologies have been proved to be efficient strategies for improving the electrochemical performances of MoO 3 -based anodes. Herein, MoO 3 /TiO 2 composites were successfully biosynthesized with different micromorphologies. In the preparation processes, the hydrothermal and solvothermal treatments were carried out successively in the presence of cellulosic filter paper as the biotemplate, followed by calcination of the as-obtained composites in air, resulting in the final MoO 3 /TiO 2 composite materials. The two microstructures of the MoO 3 microfiber with entire TiO 2 nanoparticles coating and the MoO 3 microrod formed by stacking the microsheets with loosely TiO 2 nanoparticles covering were prepared under different pH values of the precursor. Compared with the bare MoO 3 materials, the corresponding MoO 3 /TiO 2 composites showed enhanced electrochemical performances as anode materials for lithium-ion batteries. Especially the MoO 3 /TiO 2 composite with core-shell microfibrous structure derived from cellulosic filter paper presented relatively better test results for lithium storage, delivering an initial discharge capacity of 1297.6 mAh g−1 with the first Coulombic efficiency of 65.8%, and a reversible specific capacity of 403.6 mAh g−1 after 200 cycles. It is demonstrated that a well-defined TiO 2 coating layer can effectively inhibit the volume variations of MoO 3 matter in the lithiation/delithiation processes. Combined with the porous microfibrous structure that alleviates the stress, provides more reaction sites and reduces diffusion paths of lithium-ion, a promising MoO 3 -based anode material was achieved. This work provides a facile biotemplate-based strategy for the design and fabrication of metal oxide-based composites with adjustable microstructures for energy storage. [Display omitted] • Cellulosic filter paper derived MoO 3 /TiO 2 composites with variable micromorphologies were biosynthesized. • Microfibrous MoO 3 was coated by TiO 2 nanoparticles uniformly using the precursor with original pH value. • It showed enhanced reversible capacity, cycling stability and rate capability as an anode material for lithium-ion batteries. • The microstructural feature of biotemplate and the entire TiO 2 coating contribute to the improved lithium storage property. [ABSTRACT FROM AUTHOR]

Abstract: We have developed a new Si-based anode for lithium secondary batteries consisting of a carbon paper substrate and Si/C composite deposited on it (Si/C/CP electrode). The Si/C composite was formed by pyrolysis of a slurry consisting of Si power and THF solution of PVC as the carbon precursor. The electrode contains no additional conductive carbon and binder, which supports the tight contact among the Si particle, pyrolytic carbon and carbon paper. The Si/C/CP electrode with the three-dimensional carbon fiber framework of the carbon paper was also advantageous to absorb severe volume changes of silicon particles. The electrode performance revealed that the Si/C/CP electrode prepared from the mixture of Si and PVC with the ratio of 10:90 by weight had a quite high initial capacity of 1720 mAh g−1 and initial Coulombic efficiency of 90%, and also exhibited excellent capacity retention with a reversible capacity of 1200 mAh g−1 even after 100 cycles. [Copyright &y& Elsevier]

A filter-paper-derived nanofibrous silica–carbon composite composed of thin silica layer conformally coated on carbon nanofibers is synthesized by employing natural cellulose substance (ordinary laboratory filter paper) as both scaffold and carbon source. When the nanocomposite is employed as an anode material for lithium-ion batteries, it displays improved lithium-ion storage performance compared with the bare silica and carbon counter materials, due to the unique three-dimensional porous network structures of the carbon fiber scaffold and the thin silica layer. For the silica–carbon nanocomposite with 31.2 wt% of silica content and the silica layer with a thickness of ca. 60 nm, it delivers a stable discharge capacity of ca. 400 mAh g −1 after 200 discharge/charge cycles at a current density of 100 mA g −1 . Moreover, improved electrochemical performances are achieved by coverage of an additional carbon layer or deposition of silver nanoparticles onto the silica–carbon nanofibers, which exhibits specific capacities of 488.7 and 477.5 mAh g −1 after 100 discharge/charge cycles, respectively. The current synthetic method provides a facile and low-cost strategy for the large-scale production of nanofibrous silica–carbon based composites as anodic materials for lithium-ion batteries. [ABSTRACT FROM AUTHOR]

Abstract A novel and one-pot calcination method is applied for the fabrication of SnS nanoparticles coated by ultrathin carbon layer on carbon paper, resulting in a SnS/C-carbon paper free-standing electrode for lithium ion batteries. In this hierarchical structure, the carbon layer has dual function of buffering the volume change of SnS and anchoring SnS nanoparticles on the substrate compactly. Besides, it also can boost charge transfer kinetic in the electrode. Meanwhile, the carbon paper with three-dimensional structure allows for fully absorption of electrolyte and provides efficient transport pathways for electrons. Benefiting from these structure features, the binder-free SnS/C-carbon paper electrode exhibits excellent cyclability and delivers a reversible capacity of 696.2 mAh g−1 at a current density of 0.5 A g−1 after 200 cycles. Besides, SnS/C-carbon paper free-standing electrode achieves a reversible capacity of 562.3 mAh g−1 at a current density of 2.0 A g−1, demonstrating a promising rate ability which is significant for high power applicants. Such one-pot and novel route to synthesize SnS/C-carbon paper free-standing electrode with excellent electrochemical performance can pave the way for the development of low-cost and time-saving fabrication of free-standing anode for high-performance lithium ion batteries. Graphical abstract Image 1 Highlights • The carbon-coated SnS nanoparticles are directly assembled on carbon paper. • The composite is prepared by novel and one-pot calcination method. • Carbon layer anchor SnS on the substrate compactly and buffer the volume change. • The carbon paper provides sufficient transport pathways for electron and Li ion. • The electrode shows extended cycle life and excellent rate performance. [ABSTRACT FROM AUTHOR]

Abstract Lithium-Sulfur (Li-S) batteries are known for their high energy density and cost-effectiveness. However, the Li-S chemistry is a challenging topic due to the shuttle effect and the use of highly reactive lithium metal anode. To solve these issues, ultra-lightweight multilayered graphene coated paper separator is proposed as an interlayer. The interlayer is firstly coated on nickel foil by Chemical Vapor Deposition (CVD) method followed by transferring to the paper by fishing process. By employing this unique technique, a very light (∼8 μg/cm2) graphene coating layer is obtained which does not further imply lowering the entire energy density of the cell. As a whole, the cell with graphene coated paper exhibits 610 mAh/g discharge capacity at C/5 after 100 cycles, while the cell without interlayer exhibits much poorer performance. The improved performance is mostly associated with the interaction between graphene and polysulfide species which is proven by X-Ray Photoelectron Spectroscopy measurement as well as the excellent electronic conductivity of graphene layer which behaves as a secondary current collector resulting the cell resistance decrease. Graphical abstract Image 1 Highlights • Graphene is conformally coated on nickel foil by Chemical Vapor Deposition. • Graphene is transferred to paper in water by fishing process. • Graphene coating has one of the lowest weight (8 μg/cm2) used in Li-S batteries. • 610 mAh/g discharge capacity is gained after 100 cycles with graphene coated paper. [ABSTRACT FROM AUTHOR]

Although possessing well‐defined nanostructures and excellent multi‐electron redox properties, polyoxometalate clusters have poor intrinsic electrical conductivity and are prone to aggregation due to large surface energy, which makes them difficult to be fully utilized when applying as electrode materials for lithium‐ion batteries. In this paper, monodisperse K7MnV13O38 (MnV13) clusters are achieved by rationally utilizing nano‐sized high conductive carbon dots (CDs) as stabilizers. Benefiting from the fully exposed redox sites of MnV13 clusters (high utilization rate) and sufficient interfaces with carbon dots (extra interfacial energy storage), the optimized MnV13/10CDs anode delivers a high discharge capacity up to 1348 mAh g−1 at a current density of 0.1 A g−1 and exhibits superb rate/cycling capabilities. Density functional theory (DFT) calculations verify that ionic archway channels are formed between MnV13 and CDs, eliminating the bandgap and greatly improving the electron/ion conductivity of MnV13 and CDs. This paper paves a brand‐new way for synthesis of monodisperse clusters and maximization of extra interfacial energy storage. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for rapidly balancing lithium-ion batteries using a single DC–DC converter, enabling direct energy transfer between high- and low-voltage cells. Utilizing relays for cell pair selection ensures cost-effectiveness in the switch network. The control system integrates a battery-monitoring IC and an MCU to oversee cell voltage and ensure battery protection. A prototype circuit with twelve lithium-ion batteries demonstrates the method's efficacy, achieving a remarkable balancing time of 48 min during charging with a maximum efficiency of 89.85%. Comparative analysis with other methods underscores the superior performance of the proposed balancing circuit in terms of balancing time and implementation cost. Furthermore, this paper delves into hardware aspects of battery management systems (BMSs) for electric vehicles and stationary applications. It offers an overview of prevailing concepts in state-of-the-art systems, aiding readers in assessing considerations essential for BMS design in various applications. The discussion includes examples of battery packs sourced from commercially available electric vehicles. Subsequently, the manuscript addresses implementation aspects concerning the measurement of critical physical variables such as voltage, current, and temperature, alongside balancing strategies. [ABSTRACT FROM AUTHOR]

The advancement of new energy vehicles has led to more demanding standards for detecting defects in cylindrical coated lithium batteries. The current research lacks robustness and has low performance. This paper seeks to provide real-time defect identification in cylindrical coated lithium batteries and improve the object detection method of the YOLOv5s model. This paper presents an MGSEC3 module with multi-scale feature extraction and integration of the SENet network in the YOLOv5 Backbone network. This module aims to reduce computational burden and enhance feature extraction efficiency as much as possible. At the same time, the CARAFE operator is utilized to enhance the up-sampling operator in order to reduce the loss of feature information. In addition, enhancements to the loss function enhance both the detection performance and convergence speed. The enhanced YOLOv5s model achieved an average detection rate of 82.4% on the custom cylindrical coated lithium battery dataset, 2.3% higher than the original YOLOv5s. This paper significantly enhances the precision and efficiency of flaw identification in cylindrical coated lithium batteries. [ABSTRACT FROM AUTHOR]

In this paper, we design a binder GG-CA-GLY (abbreviation: GGC) for silicon negative electrode by guar gum as the backbone chain with self-healing function, combing and straightening the guar molecular chain of guar gum through the plasticizing effect of glycerol. The condensation reactions between the exposed hydroxyl sites of guar gum and the carboxyl groups of citric acid create a stronger hydrogen bond, so as to achieve the effect of self-healing and cope with the serious volume expansion effect of silicone-based materials. [Display omitted] • A easy polycondensation reaction is used to create a mechanically strong self-healing polymer (GGC). • GGC adhesives have excellent mechanical properties and facilitate rapid self-healing. • GGC@Si electrodes were prepared with excellent rate capability and higher cycling stability. • GGC adhesives have the ability to repair cracks and other damage on prepared silicon anodes, returning them to their original state. Silicon is a promising anode material for lithium-ion batteries with its superior capacity. However, the volume change of the silicon anode seriously affects the electrode integrity and cycle stability. The waterborne guar gum (GG) binder has been regarded as one of the most promising binders for Si anodes. Here, a unique steric molecular combing approach based on guar gum, glycerol, and citric acid is proposed to develop a self-healing binder GGC, which would boost the structural stability of electrode materials. The GGC binder is mainly designed to weaken van der Waals' forces between polymers through the plasticizing effect of glycerol, combing and straightening the guar molecular chain of GG, and exposing the guar hydroxyl sites of GG and the carboxyl groups of citric acid. The condensation reaction between the hydroxyl sites of GG and the carboxyl groups of citric acid forms stronger hydrogen bonds, which can help achieve self-healing effect to cope with the severe volume expansion effect of silicone-based materials. Silicon electrode lithium-ion batteries prepared with GGC binders exhibit outstanding electrochemical performance, with a discharge capacity of up to 1579 mAh/g for 1200 cycles at 1 A/g, providing a high capacity retention rate of 96%. This paper demostrates the great potential of GGC binders in realizing electrochemical performance enhancement of silicon anode. [ABSTRACT FROM AUTHOR]

The purpose of this article is is to investigate the critical speed and back-layer length of smoke propagation during fires of lithium-ion battery vehicles in tunnels. The combustion of lithium-ion battery vehicles in tunnels is numerically simulated. This article uses heat release rate (HRR) and ventilation rate to predict the length of smoke counterflow in tunnel fires with new energy vehicles. Temperature is an important parameter for calculating smoke counterflow. The temperature in the tunnel is measured by thermocouples. The results showed that dimensionless critical velocity influences dimensionless HRR. The numerical simulation results indicated that there is a certain correlation between the HRR variable, which corresponds to the dimensionless smoke counterflow length and the critical speed in the tunnel. This article proposed a computational model for predicting the length of smoke counterflow. This paper contributes to the prevention of tunnel fires and reduction of social and economic losses. Therefore, this paper guides the propagation of smoke under the roof of lithium-ion battery vehicle fires in tunnels. [ABSTRACT FROM AUTHOR]

Abstract: Tin on a carbon paper (CP) was investigated by repeated galvanostatic cycles with time-limited charges to insert different amounts of lithium per Sn atom, and tin electrodeposited on copper was also investigated for comparison of the cyclic stability. The results demonstrated that, unlike Sn electrodeposited on Cu foil, Sn on CP can undergo several tens of lithiathion/delithiation cycles with Li/Sn atomic ratio ≤2 at high current density (0.70mAcm-2), thus confirming that carbon paper is a good current collector-substrate which is able to improve the cycling performance of tin by preserving the electric contact over cycling, in spite of the great volume changes during the lithium insertion/removal processes in tin. [Copyright &y& Elsevier]

Repressing the hampers of poor electrical conductivity and pulverization is central for the applications of metal oxides anode materials, yet remains big challenge. To meet the target, pie-like graphene paper@Fe 3 O 4 nanorod arrays@carbon film is designed and fabricated as high-performance integrated electrode for lithium ion batteries. Graphene paper is selected as binder-free integrated substrate, which could accelerate electron transfer, buffer volume changes of Fe 3 O 4 , contribute to additional capacity, and endow the electrode with flexibility. The carbon film serves as the package to prevent the dissolution of Fe 3 O 4 into the electrolyte, extending the cyclic life of the integrated electrode. The architecture of Fe 3 O 4 nanorod array offers void space for volume buffer and fluid electrolyte infiltration. Based on the combined structural advantages, the present pie-like electrode with interior array architecture therefore exhibits excellent electrochemical lithium storage properties, especially large, stable, and durable cyclic performance at high current density (852 mA g −1 after 1000 cycles at 2 A g −1 ), making it a promising candidate as high-performance flexible electrode. [ABSTRACT FROM AUTHOR]

A flexible, lightweight, and high conductivity current collector is the key element that enables fabrication of a high-performance, flexible lithium-ion battery. Here, we report a thin, lightweight, and flexible lithium-ion battery that uses graphite papers deposited with nano-sized metallic layers as the current collector, LiFePO4 and Li4Ti5O12 as the cathode and anode materials, respectively, and a PE membrane soaked in LiPF6 as the separator. Using thin, flexible graphite paper as a substrate for the current collector instead of a rigid, heavy metal foil enables us to demonstrate an ultra-thin lithium-ion battery (total thickness including encapsulation layers of less than 250 μm) that also features a light weight and high flexibility. [ABSTRACT FROM AUTHOR]

A paper-supported inorganic composite (PIC) separator is prepared by spraying Al 2 O 3 particles onto both surfaces of a commercial paper substrate. The as-prepared PIC separator shows excellent thermal stability without any shrinkage at 130 °C for 30 min, superior wettability towards the electrolyte, with a contact angle of 0°, and high ionic conductivity compared with that of the conventional polyethylene (PE) separator. The graphite|LiCoO 2 full-cells with the PIC separator exhibit good cycling and rate performance. In the nail penetration tests, the pouch cell assembled with the PIC separator shows high safety characteristics. Given the advantages of the PIC separator, it is a good potential replacement for the polyolefin separators used in high-safety lithium-ion batteries. [ABSTRACT FROM AUTHOR]

Abstract: A commercial rice paper (RP) is used for the first time as a separator membrane in lithium-ion batteries. It consists of interpenetrating cellulose fibers with a diameter of about 5–40μm to form a highly porous structure. The RP is found to be electrochemically stable at a potential below 4.5V vs. Li+/Li. Several kinds of electrode materials including graphite, LiFePO4, LiCoO2 and LiMn2O4 are used to test the compatibility of the RP in Li-ion batteries and to compare with a commercial polypropylene/polyethylene/polypropylene separator membrane. The RP separator with the same thickness gives rise to a lower resistance than the commercial separator. Due to the wonderful flexibility, high porosity, low cost and excellent electrochemical performance of the RP membrane, it is promising to partially replace commercial separators in lithium-ion batteries for low power applications. [Copyright &y& Elsevier]

One key challenge in flexible batteries lies in the development of deformable/flexible electrode with high active materials mass loading and good electronic conductivity. Herein, we report such a paper-like TiO 2 /graphene-carbon nanotube hybrid electrode by a facile vacuum filtration approach. In this electrode, titania nanoparticles with uniform size (9 nm) and carbon nanotubes are embedded into graphene sheet homogeneously, forming a peculiar 3D conducting network. This feature ensures 1) a high TiO 2 mass loading (77.3 wt %, 2.93 mg cm −2 ); 2) good electric conductivity (∼1000 S m −1 ); and 3) good flexibility. Benefiting from these, the electrode delivers a high specific capacity (214 mAh g −1 ), excellent rate capability, and up to 700 cycles stability at a high rate of 1000 mA g −1 . This fabrication strategy demonstrates great practical potential and opens up new idea for high-performance self-supported electrode design. [ABSTRACT FROM AUTHOR]

Fluoroethylene carbonate (FEC)-based electrolytes using FEC as the co-solvent (50 wt%) are investigated and compared with the electrolyte using FEC as the additive (10 wt%) for freestanding Si-carbon nanotubes (CNTs) composite paper anodes for Li-ion batteries. The ethylene carbonate (EC)-free FEC-based electrolyte is found to achieve higher specific capacity and better capacity retention in terms of long-term cycling. After 500 cycles, the capacity retention of the cell using diethyl carbonate (DEC)-FEC (1:1 w/w) is increased by 88% and 60% compared to the cells using EC-DEC-FEC (45:45:10 w/w/w) and EC-FEC (1:1 w/w), respectively. Through SEM-EDX and XPS analyses, a possible reaction route of formation of fluorinated semicarbonates and polyolefins from FEC is proposed. The inferior cell performance related to the EC-containing electrolytes is likely due to the formation of more polyolefins, which do not favor Li ion migration. [ABSTRACT FROM AUTHOR]

Wrinkled-paper-like ZnCo 2 O 4 nanoflakes were synthesized by a facile hydrothermal synthesis and a post-annealing treatment. As an anode for lithium-ion batteries, it exhibits high capacity, excellent cyclability and ultrahigh rate performance. A reversible capacity of 1138 mAh g −1 at 1 A g −1 was obtained after 500 cycles. After cycled at current densities from 0.2 to 25.6 A g −1 , the reversible capacity can recover to 1089 mAh g −1 at 0.2 A g −1 . It has been demonstrated that the wrinkled-paper-like ZnCo 2 O 4 nanoflakes are promising for application as future energy storage units. [ABSTRACT FROM AUTHOR]

This study demonstrates the preparation of well aligned-carbon nanotube (WA-CNT) arrays onto a carbon paper substrate with a conductive carbon-black layer by the catalyst seed-impregnated chemical vapor deposition method. The prepared WA-CNT arrays were then characterized by scanning electron microscopy for different growth temperatures, standard linear velocities of feed vapors, and ferrocene-to-xylene ratios in the feed vapors. Results indicate that the optimal WA-CNT arrays of length 40–50 μm and diameter 30–40 nm were obtained at the growth temperature range of 750–800 °C, standard linear velocity of 1.40 cm s −1 , and ferrocene-to-xylene molar ratio of 1:50–1:30. These results provide new insights into the growth mechanism of CNT arrays, which involves cross-coupling of chemical reaction and mass transfer based on reaction engineering theory. The samples prepared in the study can be used as catalyst supports in air electrodes considering their three-dimensional porous structure, approximately linear channel, controllable length and diameter distribution, and excellent CNT conductivity. Electrochemical measurement indicated that the WA-CNT arrays/carbon-black layer/carbon paper substrate composites achieved relatively high discharge capacity of 2930 mAh g −1 (CNTs) at a current density of 0.05 mA cm −2 in Li–air batteries, which far exceeded other carbonaceous materials in Li–air batteries. [ABSTRACT FROM AUTHOR]

Battery Management System (BMS) functions to monitor individual cell in a battery pack and its crucial task is to maintain stability throughout the battery pack. The BMS is responsible for maintaining the safety of the battery as well as not to harm the user or environment. The parameters that are to be monitored in a battery are Voltage, Current and Temperature. With the collected data, BMS carefully monitors the charging–discharging behavior of the battery particularly in the Lithium-ion (Li-ion) batteries in which charging and discharging behavior are completely different. This paper proposes a real-time IOT connected deep learning algorithm for estimation of State-of-Charge (SoC) of Li-ion batteries. This paper provides unique objectives and congruence between model-based conventional methods and state-of-the-art deep learning algorithm, specifically Feed Forward Neural Network (FNN) which is nonRecurrent. This paper also highlights the advantages of Internet-of-Things (IoT) connected deep learning algorithm for estimation of State-of-Charge of Li-ion batteries in Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs). The major advantage of the proposed method is that the Artificial Intelligence (AI)-based techniques aim to bring the estimation error less than 2% at a low cost and time without the model of the battery, at par with conventional method of Extended Kalman Filter (EKF) which is the best ever practical estimation theory. Another advantage of the proposed method is that in an abnormal condition (i.e., Unsafe Temperature) the IF This Then That (IFTTT) IoT mobile application interfaced with BMS through ThingSpeak cloud, sends a notification alert to the battery expert or to the user prior to an emergency. Finally, the real-time data of the battery parameters are collected through ThingSpeak cloud platform for future research and analysis. [ABSTRACT FROM AUTHOR]

Accurately assessing the state of health (SOH) of lithium batteries is of great significance for improving battery safety performance. However, the current assessment for SOH suffers from the difficulty of selecting health features and the lack of uncertainty using data-driven methods. To this end, this paper proposes a health state assessment method for lithium-ion batteries based on health feature extraction and an improved Informer model. First, multiple features that can reflect the SOH of lithium-ion batteries were extracted from the charging and discharging time, the peak value of incremental capacity curve (ICC), and the inflection point value of differential voltage curve, etc., and the correlation between multiple health features and the health state was evaluated by gray correlation analysis. Then, an improved Informer model is proposed to establish a health state estimation method for lithium-ion batteries. Finally, the proposed algorithm is tested and validated using publicly available battery charge/discharge datasets and compared with other algorithms. The results show that the method in this paper can realize high-precision SOH prediction with a root-mean-square error (RMSE) of 0.011, and the model fit reaches more than 98%. [ABSTRACT FROM AUTHOR]

The escalating worldwide power demand necessitates innovative solutions to address the emerging power crisis. Grid-synchronized electric vehicles (EVs) have emerged as a promising avenue for mitigating this crisis. The vehicle-to-grid technology is unique advanced smart grid concept by which the exchange of energy is allowed among grid and EV. The integration of EV and grid affects an entire power system causing imbalance in supply–demand, voltage and frequency. To minimize these issues, feasible optimization techniques are introduced in this paper. Lithium-ion batteries are initially charged via smart homes, and convolutional neural networks (CNN) are used to ascertain a battery's state of charge (SOC). A bidirectional SEPIC–zeta converter is employed in this paper by which voltage is either increased or decreased. The gating sequence for the converter is generated by means of adaptive neuro fuzzy inference system which depends on an estimated SOC. If the SOC is greater than 80%, battery is discharged using a SEPIC mode; if the SOC is lower than 80%, battery is charged by grid using the ZETA mode. By using a PI controller, active and reactive power are also controlled. Simulation results using MATLAB showcase the efficacy of the suggested approach. The bidirectional SEPIC–Zeta converter exhibits an impressive efficiency of 96% and a voltage gain ratio of 1:8 when compared to other converters. CNN-based SOC tracking achieves remarkable tracking efficiency of 92.3%, outperforming other tracking methods. The grid current total harmonic distortion is notably curtailed at 2.3%, and a power factor of 0.9 is achieved using PI-based grid synchronization. [ABSTRACT FROM AUTHOR]

Highlights: Research progress of advanced optical fiber sensors in traction batteries and energy storage batteries is summarized. The embedded application mechanisms of different optical fiber sensors in batteries are discussed. Advanced optical fiber sensors adapting to batteries with diverse materials are reviewed. Advanced optical fiber sensors driving the development of future smart batteries are prospected. The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist. Now the battery is still a "black box", thus requiring a deep understanding of its internal state. The battery should "sense its internal physical/chemical conditions", which puts strict requirements on embedded sensing parts. This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed, focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano–micro-level battery material structural phase transition, electrolyte degradation, electrode–electrolyte interface dynamics to three-dimensional macro-safety evolution. The paper contributes to understanding how to use optical fiber sensors to achieve "real" and "embedded" monitoring. Through the inherent advantages of the advanced optical fiber sensor, it helps clarify the battery internal state and reaction mechanism, aiding in the establishment of more detailed models. These advancements can promote the development of smart batteries, with significant importance lying in essentially promoting the improvement of system consistency. Furthermore, with the help of smart batteries in the future, the importance of consistency can be weakened or even eliminated. The application of advanced optical fiber sensors helps comprehensively improve the battery quality, reliability, and life. [ABSTRACT FROM AUTHOR]

The battery pack is at the heart of electric vehicles, and lithium-ion cells are preferred because of their high power density, long life, high energy density, and viability for usage in relatively high and low temperatures. Lithium-ion batteries are negatively affected by overvoltage, undervoltage, thermal runaway, and cell voltage imbalance. The minimisation of cell imbalance is particularly important because it causes uneven power dissipation by each cell and, hence, temperature distribution that adversely impacts the battery lifetime. Several papers in the literature proposed advanced cell-balancing techniques to increase the effectiveness of basic cell-balancing approaches, reduce power losses, and reduce the number of components in balancing circuits. The new developments and optimisations over the last few years have been particularly intense due to the increased interest in battery technologies for several end-use applications. This paper reviews and discusses recent cell-balancing techniques or methods, covering their operating principles and the optimised utilisation of electrical components. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have garnered significant attention as a vital driver of economic growth and environmental sustainability. Nevertheless, ensuring the safety of high-energy batteries is now a top priority that cannot be overlooked during large-scale applications. This paper proposes an innovative active protection and cooling integrated battery module using smart materials, magneto-sensitive shear thickening fluid (MSTF), which is specifically designed to address safety threats posed by lithium-ion batteries (LIBs) exposed to harsh mechanical and environmental conditions. The theoretical framework introduces a novel approach for harnessing the smoothed-particle hydrodynamics (SPH) methodology that incorporates the intricate interplay of non-Newtonian fluid behavior, capturing the fluid-structure coupling inherent to the MSTF. This approach is further advanced by adopting an enhanced Herschel-Bulkley (H-B) model to encapsulate the intricate rheology of the MSTF under the influence of the magnetorheological effect (MRE) and shear thickening (ST) behavior. Numerical simulation results show that in the case of cooling, the MSTF is an effective cooling medium for rapidly reducing the temperature. In terms of mechanical abuse, the MSTF solidifies through actively applying the magnetic field during mechanical compression and impact within the battery module, resulting in 66% and 61.7% reductions in the maximum stress within the battery jellyroll, and 31.1% and 23% reductions in the reaction force, respectively. This mechanism effectively lowers the risk of short-circuit failure. The groundbreaking concepts unveiled in this paper for active protection battery modules are anticipated to be a valuable technological breakthrough in the areas of EV safety and lightweight/integrated design. [ABSTRACT FROM AUTHOR]

Abstract: Carbon coated silicon (Si/C) dispersed in a carbon paper (CP) was examined as the anode for solid polymer lithium-ion batteries. The CP was prepared by pyrolysis of poly(acrylonitrile) fiber and Manila hemp non-woven cloth at 2600 °C under an inert atmosphere. The Si/C composite was formed by pyrolysis of a slurry consisting of Si power and a solution of polyvinyl chloride in tetrahydrofuran as the carbon source. Si/C:CP with a weight ratio of 20:100 had a high initial capacity of 980 mAh g−1 of Si/C and a high initial columbic efficiency of 77%, and also exhibited excellent capacity retention with a reversible capacity of 710 mAh g−1 of Si/C even after 250 cycles at a charge and discharge rate of 0.1 A g−1. The carbon fiber framework in the carbon paper could adsorb the volume change of Si during the lithium insertion and stripping processes. [Copyright &y& Elsevier]

Designing a high capacity and long cycle life MnO-based composite material for lithium ion batteries (LIBs) is still a great challenge because of the intrinsically low electrical conductivity and dramatic volume variations during lithiation/delithiation. In this paper, the MnO nanoparticles (MnO NPs) are recombined with multi-walled carbon nanotubes (MWCNTs) and reduced graphene oxide (r-GO) to rationally construct a novel MnO NPs@MWCNTs/r-GO multilayer sandwich structure via electrostatic interaction self-assembly and vacuum filtration processes. As a result, the MnO NPs are closely attracted in the conductive MWCNTs network, and the MWCNTs adsorbed on the surface of MnO NPs can be served as a soft and flexible carbon coating layer to self-adapt the huge volume expansion. For another, the r-GO between two MnO NPs@MWCNTs layers is the cause to form a free-standing paper, enhancing the transverse conductivity of the whole electrode simultaneously. These features will contribute to achieve excellent cycling stability and improved rate capability. [ABSTRACT FROM AUTHOR]

A flexible Bi 2 Se 3 /Graphene (BSG) composite paper has been prepared through a simple vacuum filtration method and a thermal reduction together. The BSG composite paper was directly used as anode electrode for lithium-ion batteries, without using any polymer binders or conduction additives. In contrast to the pure Bi 2 Se 3 , the BSG exhibits high reversible lithium ion storage capacities and superior cyclic capacity retention. It proposed that the superior lithium storage performances would be attributed to the special construction of the as-prepared BSG paper, in which the graphene can not only act as conductive network for electrodes, but also act as a frame to alleviate volume expansion or aggregation of Bi 2 Se 3 nanosheets during lithiation/delithiation. The as-prepared BSG paper shows a great potential as an anode materials for flexible Li-ion batteries. [ABSTRACT FROM AUTHOR]

This work presents a novel binder-free nitrogen-doped carbon paper electrode (NCPE), which was derived from a N-rich polypyrrole (PPy)/cellulose-chopped carbon filaments (CCFs) composite, for Li–O 2 batteries. The fabrication of NCPE involved cheap raw materials ( e.g., Cladophora sp. green algae) and easy operation ( e.g., doping N by a carbonization of N-rich polymer), which is especially suitable for large-scale production. The NCPE exhibited a bird's nest microstructure, which could provide the self-standing electrode with considerable mechanic durability, fast Li + and O 2 diffusion, and enough space for the discharge product deposition. In addition, the NCPE contained N-containing function groups, which may promote the electrochemical reactions. Furthermore, binder-free architecture designs can prevent binder-involved parasitic reactions. A Li–O 2 cell with the NCPE displayed a cyclability of more than 30 cycles at a constant current density of 0.1 mA/cm 2 . The 1st discharge capacity for a cell with the NCPE reached 8040 mAh/g at a current density of 0.1 mA/cm 2 , with a cell voltage around 2.81 V. A cell with the NCPE displayed a coulombic efficiency of 81% on the 1st cycle at a current density of 0.2 mA/cm 2 . These results represent a promising progress in the development of a low-cost and versatile paper-based O 2 electrode for Li–O 2 batteries. [ABSTRACT FROM AUTHOR]

Silicon has been considered as one of the most promising anode materials for the next generation lithium-ion battery due to its high theoretical capacity, but large volume changes during the electrochemical cycling limit its commercial application. In this study, we report the synthesis of silicon carbide @ silicon core–shell nanowires on carbon paper and their application in lithium-ion batteries. The hybrid nano-structures are fabricated via a two-step chemical vapor deposition method and directly used as the working electrode without any additional binder, exhibiting high specific capacity, high coulombic efficiency and good cycling stability. After 50 cycles, the discharge capacities still remain 2837 and 1809 mAh g −1 at the rates of 0.1C and 0.5C, respectively. Furthermore, we also study the influence of the growth time of SiC NWs and the thickness of Si film on the lithium-ion batteries' performance, and propose the possible method to further improve the battery performance. [ABSTRACT FROM AUTHOR]

Abstract: Porous structure-tuned cellulose nanofiber paper separators (designated as S-CNP separators) are demonstrated as a promising alternative to commercial polyolefin separators for use in lithium-ion batteries. A new architectural strategy based on colloidal silica (SiO2) nanoparticle-assisted structural control is presented to overcome the difficulty in forming controllable porous structure of pure cellulose nanofiber paper separators (designated as CNP separators) from densely-packed cellulose nanofibers (CNFs). The new S-CNP separators proposed herein incorporate SiO2 nanoparticles as a CNF-disassembling agent (i.e., as non-conductive spacer particles). This structural uniqueness allows loose packing of CNFs, thereby facilitating the evolution of more porous structure. The unusual porous structure of S-CNP separators can be fine-tuned by varying SiO2 contents in the CNF suspension. Notably, the S-CNP separator (fabricated with 5 wt.% SiO2 content) exhibits the highest ionic conduction due to the well-balanced combination of nanoporous structure and separator thickness, thus contributing to excellent cell performance. This study underlines that the colloidal SiO2 nanoparticle-directed structural tuning of CNPs offers a promising route for the fabrication of advanced paper separators with optimized attributes and functionality. [Copyright &y& Elsevier]

[Display omitted] Silicon is considered as the next-generation anode material for lithium-ion batteries due to its high theoretical specific capacity and abundant crustal abundance. However, its poor electrical conductivity results in slow diffusion of lithium ions during battery operation. Simultaneously, the alloying process of silicon undergoes a 300 % volume change, leading to structural fractures in silicon during the cycling process. As a result, it loses contact with the current collector, continuously exposing active sites, and forming a sustained solid electrolyte interface (SEI) membrane. This paper presents the design of a fluorine-ion-regulated yolk–shell carbon-silicon anode material, highlighting the following advantages: (a) Alleviating volume changes through the design of a yolk–shell structure, thereby maintaining material structural integrity during cycling. (b) Carbon shell prevents silicon from coming into contact with the electrolyte, simultaneously improving silicon's electrical conductivity and increasing ion/electron conductivity. (c) Utilizing fluorine-ion interface modification to obtain an SEI membrane rich in fluorine components (such as LiF), thereby enhancing its long cycling performance. The F-Si@Void@C exhibits outstanding electrochemical performance, with a reversible capacity of 1166 mAh/g after 900 cycles at a current density of 0.5 A/g. [ABSTRACT FROM AUTHOR]

The accurate health status evaluation of lithium-ion batteries is crucial for preemptive identification of potential battery failures and averting hazardous incidents, given its essential role in indicating the extent of battery degradation. The challenge in determining the State of Health (SOH) arises from the absence of a precise and standardized definition, as well as the difficulty in measuring essential input variables. Therefore, this paper utilizes current and voltage data during the charge and discharge process as direct inputs for SOH estimation and proposes a deep learning-based lithium-ion battery SOH estimation approach. Specifically, it leverages Bayesian optimized Convolutional Neural Network (CNN) within a data-driven framework. Experimental results demonstrate that the proposed deep learning method achieves a Mean Absolute Error (MAE) of 1% and a Maximum Error (MAX) below 4% in estimation accuracy, highlighting its enhanced precision and robustness. [ABSTRACT FROM AUTHOR]

Accurately predicting the state of health (SOH) of lithium-ion batteries is fundamental in estimating their remaining lifespan. Various parameters such as voltage, current, and temperature significantly influence the battery's SOH. However, existing data-driven methods necessitate substantial data from the target domain for training, which hampers the assessment of lithium-ion battery health at the initial stage. To address these challenges, this paper introduces the multi-head attention-time convolution network (MHAT-TCN), amalgamating multi-head attention learning with random block dropout techniques. Additionally, it employs grey relational analysis (GRA) to select health indicators (HIs) highly correlated with battery capacity, thereby enhancing the accuracy of the model training. Employing leave-one-out crossvalidation (LOOCV), the MHAT-TCN network is pre-trained using data from batteries of the same model to facilitate comprehensive prediction of the target battery throughout its operational period. Results demonstrate that the MHAT-TCN network trained on HIs outperforms other models, enabling precise predictions across the entire operational period. [ABSTRACT FROM AUTHOR]

Monitoring the health of lithium batteries is a crucial undertaking in ensuring the safe and dependable functioning of electric vehicles. Data‐driven methods have been proved to be an effective method for identifying the complex degradation process of batteries. To augment the precision of predicting the remaining useful life (RUL), this paper introduces a pioneering architecture for a denoising autoencoder (DAE). This architecture integrates a stacked convolutional neural network with subsequent layers of bidirectional gated recurrent units within an encoder–decoder framework. The utilization of the DAE network is employed as a means to effectively capture and represent the intricate and nonlinear knowledge associated with degradation data acquired from measured sources. Simultaneously, the reconstruction loss is incorporated into the total loss to improve the accuracy and generalization of the prediction model. The efficacy of the proposed approach is substantiated through the utilization of data sets sourced from the NASA Ames Prognostics Data Repository. The comparative findings suggest that the proposed approach demonstrates an exceptional ability to achieve precise and robust estimation in predicting the RUL, surpassing other advanced methodologies. [ABSTRACT FROM AUTHOR]

Since solid electrolytes have a broad electrochemical stability window, are exceptionally electrochemically stable against Li metal, and function as a physical separator to prevent dendrite growth, they are at the forefront of alternate possibilities, further increasing the stability and energy density of Li-ion batteries. NASICON-type electrolytes are a promising candidate due to their negligible moisture sensitivity, which results in outstanding stability and a lower probability of Li2CO3 passivity under the ambient atmosphere. However, one of the most promising representatives, Li1+xYxZr2−x(PO4)3 (LYZP), has multiple stable phases with significant variation in their corresponding Li-ion conductivity. In this paper, we have successfully synthesized the highly ionically conductive rhombohedral phase of LYZP via spray-flame synthesis. Two different solvent mixtures (e.g., 2-ethyl hexanoic acid/ethanol, propanol/propanoic acid) were chosen to explore the effect of precursor composition and combustion enthalpy on the phase composition of the nanoparticle. The as-synthesized nanoparticles from spray-flame synthesis consisted of the crystalline tetragonal zirconia (t-ZrO2) phase, while lithium, yttrium, and phosphate were present on the nanoparticles' surface as amorphous phases. However, a short annealing step (1 h) was sufficient to obtain the NASICON phase. Moreover, we have shown the gradual phase conversion from orthorhombic β phase to rhombohedral α phase as the annealing temperature increased from 700 °C to 1300 °C (complete removal of β phase). In this context, Y3+ doping was also crucial, along with the appropriate solvent mixture and annealing temperature, for obtaining the much-desired rhombohedral α phase. Further, 0.2 at% Y3+ doping was added to the solvent mixture of 2-ethyl hexanoic acid/ethanol, and annealing at 1300 °C for 1 h resulted in a high ionic conductivity of 1.14∙10−5 S cm−1. [ABSTRACT FROM AUTHOR]

This paper proposes a novel physics-based equivalent circuit model of the lithium-ion battery for electric vehicle applications that has comprehensive electrochemical significance and an acceptable level of complexity. Initially, the physics-based extended single particle (ESP) model is improved by adding a correction term to mitigate its voltage bias. Then, the equivalent circuit model based on the improved extended single particle (ECMIESP) model is derived. In this model, the surface state of charge (SOC) of solid particles is approximated using a capacity and multi first-order resistance-capacity equivalent circuits with only two lumped parameters. The overpotential of electrolyte diffusion is approximated using a first-order resistance-capacitance equivalent circuit. The electrochemical reaction overpotential is characterized by a nonlinear resistance. The voltage accuracies of ECMIESP and conventional 2RC equivalent circuit model (ECM2RC) are compared across the entire SOC range under various load profiles. The results demonstrate that the ECMIESP model outperforms ECM2RC model, particularly at low SOC or when the electrochemical reaction overpotential exceeds 50 mV. For instance, the ECMIESP model shows an 820.4 mV reduction in voltage error compared to the ECM2RC model at the endpoint during a 2C constant current discharge test. Lastly, the ECMIESP model was used for SOC estimation with extended Kalman filter, resulting in significantly improved accuracy compared to the conventional ECM2RC model. Therefore, the ECMIESP model has great potential for real-time applications in enhancing voltage and SOC estimation precision. [ABSTRACT FROM AUTHOR]

In response to the dual carbon policy, the proportion of clean energy power generation is increasing in the power system. Energy storage technology and related industries have also developed rapidly. However, the life-attenuation and safety problems faced by energy storage lithium batteries are becoming more and more serious. In order to clarify the aging evolution process of lithium batteries and solve the optimization problem of energy storage systems, we need to dig deeply into the mechanism of the accelerated aging rate inside and outside the lithium ion from the perspective of the safety and stability of a lithium battery in view of the complex and changeable actual working conditions during the operation of the battery. This paper takes a lithium-iron phosphate battery and a lithium-ion battery as examples to analyze. According to the specific scene of lithium battery operation, the actual operating conditions of lithium battery environmental impact factors and attenuation mechanisms are described in detail. The damage to the internal structure of lithium batteries was systematically analyzed. Furthermore, the correlation between the external influencing factors and the aging rate of lithium batteries under the coupling effect of internal failure mechanisms is analyzed. Finally, future energy storage failure analysis technology is anticipated, hoping to play a positive role in promoting the development of energy storage and lithium battery failure analysis technology. [ABSTRACT FROM AUTHOR]

This paper presents a capacity planning framework for a microgrid based on renewable energy sources and supported by a hybrid battery energy storage system which is composed of three different battery types, including lithium-ion (Li-ion), lead acid (LA), and second-life Li-ion batteries for supplying electric vehicle (EV) charging stations. The objective of this framework is to determine the optimal size for the wind generation systems, PV generation systems, and hybrid battery energy storage systems (HBESS) with the least cost. The framework is formulated as a mixed integer linear programming (MILP) problem, which incorporates constraints for battery ageing and the amount of unmet load for each year. The system uncertainties are managed by conducting the studies for various scenarios, generated and reduced by generative adversarial networks (GAN) and the k-means clustering algorithm for wind speed, global horizontal irradiation, and EV charging load. The studies are conducted for three levels of unmet load, and the outputs are compared for these reliability levels. The results indicate that the cost of hybrid energy storage is lower than individual battery technologies (21% compared to Li-ion, 4.6% compared to LA, and 6% compared to second-life Li-ion batteries). Additionally, by using HBESS, the capacity fade of LA batteries is decreased (for the unmet load levels of 0, 1%, 5%, 4.2%, 6.1%, and 9.7%, respectively), and the replacement of the system is deferred proportional to the degradation reduction. [ABSTRACT FROM AUTHOR]

The global transportation system's need for electrification is driving research efforts to overcome the drawbacks of battery electric vehicles (BEVs). The accurate and reliable estimation of the states of charge (SOC) and health (SOH) of Li-Ion batteries (LIBs) is crucial for the widespread adoption of BEVs. Transformers, cutting-edge deep learning (DL) models, are demonstrating promising capabilities in addressing various sequence-processing problems. This manuscript presents a thorough survey study of previous research papers that introduced modifications in the development of Transformer-based architectures for the SOC and SOH estimation of LIBs. This study also highlights approximately 15 different real-world datasets that have been utilized for training and testing these models. A comparison is made between the architectures, addressing each state using the root mean square error (RMSE) and mean absolute error (MAE) metrics. [ABSTRACT FROM AUTHOR]

In this paper, a novel optimization method is proposed based on the sparrow search algorithm, namely, multi-strategy-guided sparrow search algorithm (MGSSA). It is well-known that the basic SSA has limitations such as the slow convergence speed and vulnerability to local optimality. Surrounding these two issues, some strategies are presented in the MGSSA. Firstly, the newly introduced ring topology search strategy not only maintains the diversity of the entire population but also enhances the exploration ability of the SSA. Secondly, the proposed leader-based search strategy can improve exploitation ability of the SSA to prevent falling into local optimum as much as possible. Moreover, the coordinated learning strategy is put forward to better balance between the exploration and exploitation abilities. Finally, the MGSSA is compared with seventeen advanced algorithms on two well-known benchmark suites (i.e., CEC-2017 and CEC-2020). Meanwhile, the MGSSA-based forecasting approach is applied to predict the remaining useful life for lithium-ion batteries. The statistical results indicate that the MGSSA is a high-performance optimizer, which can not only solve the defects of the original SSA, but also obtain satisfactory solutions in both complex numerical optimization and real-world application problems. [ABSTRACT FROM AUTHOR]

Accurately estimating Battery State of Charge (SOC) is essential for safe and optimal electric vehicle operation. This paper presents a comparative assessment of multiple machine learning regression algorithms including Support Vector Machine, Neural Network, Ensemble Method, and Gaussian Process Regression for modelling the complex relationship between real-time driving data and battery SOC. The models are trained and tested on extensive field data collected from diverse drivers across varying conditions. Statistical performance metrics evaluate the SOC prediction accuracy on the test set. Gaussian process regression demonstrates superior precision surpassing the other techniques with the lowest errors. Case studies analyse model competence in mimicking actual battery charge/discharge characteristics responding to changing drivers, temperatures, and drive cycles. The research provides a reliable data-driven framework leveraging advanced analytics for precise real-time SOC monitoring to enhance battery management. [ABSTRACT FROM AUTHOR]

With the increase in the amount of actual operating data on electric vehicles, how to analyze and process useful information from existing battery charging and discharging data and apply it to subsequent state estimation is worthy of in-depth thinking and practice by researchers. This article proposes a collaborative estimation architecture for SOC and SOH based on the 1RC equivalent circuit model, recursive least squares, and adaptive extended Kalman filtering algorithms (AEKF), which combine offline data processing with online applications. By applying offline data processing, OCV–SOC polynomial fitting and average polarization resistance were determined, which reduced the time required for basic data measurement and improved the accuracy of model parameter identification, while a recursive estimation combining micro- and macro-time-scales of AEKF was used for the online real-time estimation of the SOC and actual available capacity of batteries, in order to eliminate interference from measurement and process noise. The results of the simulated and experimental data validation indicate that the proposed algorithm is applicable to the lithium-ion batteries studied in this paper, the average SOC deviation is less than 1.5%, the maximum deviation is less than 2.02%, and the SOH estimation deviation is less than 1% under different driving conditions in the multi-temperature range. This study lays the foundation for further utilizing offline data and improving SOC and SOH collaborative estimation algorithms. [ABSTRACT FROM AUTHOR]