Energy Lithium-ion Batteries Research Articles

Realization of building grade fire resistance in independent fire zone of energy storage system

Abstract Lithium battery energy storage technology is one of the most promising technologies in the field of energy storage. The fire prevention and control of energy storage system usually needs to consider the cooperation of various parts of the energy storage system. The domestic standard requirements for the fire resistance of energy storage system have not been completely established. In this paper, combined with the US standard and related fire resistance experimental standards, the relevant requirements and test methods for the fire insulation performance of battery cabinet of the energy storage system are studied, and a set of structural design methods and test schemes for the 2h fire resistance limit of the energy storage system are formed. The research shows that the fire insulation of the battery cabin has positive significance for reducing the energy consumption of the air conditioning of the energy storage product, improving the battery life, and enhancing the safety performance of the energy storage system. It is of great significance to study the suitable fire resistance limit of energy storage products for improving the land utilization rate of energy storage system and saving the construction cost.

Long Noncoding RNA NR_030777 Alleviates Cobalt Nanoparticles-Induced Neurodegenerative Damage by Promoting Autophagosome-Lysosome Fusion.

Potential exposure to cobalt nanoparticles (CoNPs) occurs in various fields, including hard alloy industrial production, the increasing use of new energy lithium-ion batteries, and millions of patients with metal-on-metal joint prostheses. Evidence from human, animal, and in vitro experiments suggests a close relationship between CoNPs and neurotoxicity. However, a systematic assessment of central nervous system (CNS) impairment due to CoNPs exposure and the underlying molecular mechanisms is lacking. In this study, we found that CoNPs induced neurodegenerative damage both in vivo and in vitro, including cognitive impairment, β-amyloid deposition and Tau hyperphosphorylation. CoNPs promoted the formation of autophagosomes and impeding autophagosomal-lysosomal fusion in vivo and in vitro, leading to toxic protein accumulation. Moreover, CoNPs exposure reduced the level of transcription factor EB (TFEB) and the abundance of lysosome, causing a blockage in autophagosomal-lysosomal fusion. Interestingly, overexpression of long noncoding RNA NR_030777 mitigated CoNPs-induced neurodegenerative damage in both in vivo and in vitro models. Fluorescence in situ hybridization assay revealed that NR_030777 directly binds and stabilizes TFEB mRNA, alleviating the blockage of autophagosomal-lysosomal fusion and ultimately restoring neurodegeneration induced by CoNPs in vivo and in vitro. In summary, our study demonstrates that autophagic dysfunction is the main toxic mechanism of neurodegeneration upon CoNPs exposure and NR_030777 plays a crucial role in CoNPs-induced autophagic dysfunction. Additionally, the proposed adverse outcome pathway contributes to a better understanding of CNS toxicity assessment of CoNPs.

Optimization of wind farm energy supply system costs through machine learning

At present, the energy crisis is becoming increasingly severe, and changing the energy structure and developing clean energy have gradually become the consensus of the world. Establishing a clean energy power supply system, using clean energy for power generation, and investing in real power supply are currently unresolved challenges. Based the current high cost of new energy power supply systems, this project proposes an optimization plan based on the wind power supply system, targeting the capacity of lithium battery energy storage equipment, and constructs an optimization model for wind power supply in electric vehicle systems. In addition, in order to use lithium-ion battery devices more efficiently and ensure the evaluation of the efficiency and battery life of lithium-ion battery energy storage devices, we predicted the cyclic aging phenomenon of lithium-ion battery energy storage devices through machine learning technology. This prediction can provide suggestions and references for the use of this lithium battery.

A deep learning model for predicting the state of energy in lithium-ion batteries based on magnetic field effects

The state of energy (SOE) is one of the most critical state indicators in battery management systems. However, its nonlinear characteristics present significant challenges in obtaining accurate SOE. Especially when applying different magnetic field strengths to perform battery charging and discharging tests, the change in battery energy becomes more complex due to the influence of the magnetization effect. In this paper, a deep learning network, combining an improved Informer and long short-term memory network (LSTM), was developed to estimate the SOE of lithium-ion batteries under different magnetic fields. First, we improve the decoder structure by adding a convolutional module using residual connections with trainable weight parameters to capture hidden states with more details.The improved decoder does not require label history information for decoding, which improves the generalization ability of the model. Finally, the output of the Informer network is a higher-dimensional hidden feature that is input into the LSTM network layer to output the SOE prediction value, which improves the original Informer network's ability to integrate sequences. Experiments with magnetic field and public datasets show the improved Informer-LSTM network achieves 0.31 % MAE, 0.42 % RMSE, and 1.79 % maximum error in SOE estimation, outperforming others in short sequence predictions.

Research on Lithium Battery Recycling and Utilization

With the rapid development of new energy, lithium batteries, as one of the key technologies in the field of energy storage, play an important role. However, with the widespread application of lithium batteries, the problem of their disposal has become increasingly prominent, which not only affects the environment but also wastes precious resources. This article analyzes the domestic new energy lithium battery market situation and finds that domestic new energy is developing rapidly and the lithium battery market has huge potential. In terms of lithium battery recycling and utilization, comparison shows that foreign lithium battery recycling technology is relatively mature, but there are certain challenges in adapting to domestic actual conditions and cost control. Although there are some advanced recycling technologies in China, the overall level still needs to be improved.

Garnet solid-state electrolyte: A new single-step elaboration by electric arc-melting

The garnet Li7-xLa3Zr2-xTaxO12 (LLZTO) has attracted a real scientific interest in the last decade as it is one of the safest solid-state electrolytes for next generation high energy lithium batteries. However, its elaboration requires several steps from phase stabilization to densification of the part. This final step, with long and high temperature treatment induces lithium loss due to sublimation. Electric arc-melting allows short time elaboration of dense parts in one-step, eventually minimizing Li sublimation. Thus, the synthesis by arc-melting of LLZTO is exposed here. Stabilized phases and microstructures are studied depending on chemical composition and casting parameters. The direct obtaining of dense parts instead of powder allows better moisture stability thanks to fast growth of protective layer preventing in-depth penetration of the H+/Li+ exchange. Finally, ionic conductivity of fused parts is in a similar range to sintered pellets produced using Spark Plasma Sintering with powdered fused parts. Those results confirm the interest of electric arc-melting synthesis as an alternative LLZTO elaboration.

Multidimensional hollow SiO2/C nanofibers modified by magnetic nanocrystals for electromagnetic energy conversion and lithium battery storage

Multidimensional hollow SiO2/C nanofibers modified by magnetic nanocrystals for electromagnetic energy conversion and lithium battery storage

Multi-level anomaly detection of lithium battery energy storage system

Abstract The energy storage technology route represented by lithium battery energy storage strongly supports China’s energy structure transformation. The widespread use of lithium batteries also poses a significant safety risk that is often overlooked. Energy storage system security is facing severe challenges. It is very beneficial for the safety of energy storage systems to predict the potential faults of lithium batteries before they are used and find anomaly batteries in time. This paper proposes a three-stage anomaly detection method based on statistics and density concepts to provide real-time potential fault prediction of lithium battery energy storage systems. Considering both efficiency and accuracy, this method can detect anomaly samples from shallow to deep. Finally, the battery condition of a large energy storage plant was studied, and 11 anomaly batteries were detected. The proposed method is significant for safely operating large energy storage power stations.

Risk analysis of lithium battery energy storage systems under typical failures

Abstract With the rapid increase in the proportion of new energy installed capacity, to solve the problem of new energy output volatility, lithium-ion battery energy storage has developed rapidly by its electrical characteristics and economic advantages and has become a hot spot for the large-scale application of electrochemical energy storage, but it is also accompanied by safety problems such as battery short-circuit and thermal runaway. Based on the typical structure of the lithium battery energy storage system, this paper establishes a complete simulation model of the lithium battery energy storage system, calculates the change rule of battery system electrical parameters inside the battery module under different types of short-circuit faults, and summarizes the fault characteristics and risks of lithium battery energy storage system under different faults. The study shows that short-circuit faults inside the battery module will cause significant fluctuations in the terminal voltage and current of the battery system. The internal short-circuit faults will increase the inter-cluster circulating current. In contrast, the larger short-circuit current will not only cause the local battery cells to overcharge and over-discharge but also trigger the thermal runaway of the battery system.

Improved ADRC Current Low‐Frequency Ripple Suppression Strategy Based on VFNF

AbstractIn the two‐stage inverter system, due to the space vector modulation (SVM), the midpoint potential of active neutral point clamped three‐level inverter system (ANPC‐TLIS) will have triple frequency fluctuation, under the influence of the closed‐loop control strategy, the fluctuation amplitude of the lithium battery energy storage system (LBESS) output current will increase. To reduce the low‐frequency output current fluctuation, a voltage loop strategy based on active disturbance rejection control (ADRC) with notch filter (NF)is proposed in this paper. In this scheme, the voltage outer‐loop control strategy not only maintains voltage stability, but also reduces the fluctuation amplitude of reference current. In addition, during the electromagnetic transient process, the LBESS output current fluctuation frequency is constantly changing because the power supply frequency required by linear motor is constantly changing. To solve this problem, the inverter output current frequency is feedforward to the LBESS controller, forming a variable frequency notch filter (VFNF). Finally, the effectiveness of the proposed strategy is verified by fixed‐frequency and variable frequency conditions experiments on RT‐LAB experimental platform. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Continuum insight into the effects of electrode design parameters on the electrochemical performance of lithium-ion batteries

Lithium-ion batteries energy and power density strongly depend on the type of active material and the electrode design parameters. An in-depth understanding of the effect of battery design parameters on their electrochemical performance is experimentally expensive and hence requires the utilization of cheaper continuum scale models. Here, using a lithium-ion cell composed of LiFePO4 cathode, Li4Ti5O12 anode and a porous separator filled with a liquid electrolyte as an example, we demonstrate the use of an experimentally validated pseudo-two-dimensional (P2D) model in one-dimension to explore the effects of different cell design parameters on the discharge capacity at different current rates. The model is simulated in two-dimensional to instantly visualize the concentration distribution of Li ions in the electrode at high discharge current rates. The continuum model unravels that the solution phase diffusion limitation is the main factor inhibiting the performance of thick electrodes at high current rates and the Li4Ti5O12 anode is the limiting electrode. These findings using continuum models provide guidance for and accelerate the optimization of electrode architecture for enhancing the performance of lithium-ion batteries.

A groovy laser processing route to achieving high power and energy lithium-ion batteries

3D-structured NMC622 with precisely controlled electrolyte channels were manufactured by incorporating femtosecond laser processing with conventional slurry casting. Demonstrated in a full cell for the first time, the 3D electrode structures mitigate plating and dendrite growth at the graphite electrode and lead to improved cycling performance, 75 % capacity retention vs 58 % after 500 cycles. 3D-structured NMC622 with a high areal capacity, 5.5 mAh cm−2, exhibits an areal capacity retention of ∼70 % and volumetric capacity exceeding 250 mAh cm−3 at ∼1.15C, three times and twice that of a conventional slurry-casted NMC622, respectively. The improved rate performance is attributed to the enhanced ionic transport and reduced charge transfer resistance facilitated by the 3D electrode structure, as shown through galvanostatic titration measurements. A finite element method-based 3D model illustrated the improved uniform distribution of Li-ion concentration and state of charge within the 3D-structured electrode. Additionally, the 3D electrode structure proved beneficial for wettability and accelerated electrolyte absorption, leading to improved manufacturing efficiency.

Adsorption behavior of CuO doped GeS monolayer on the thermal runaway gas evolution in lithium battery energy storage systems

Considering that the thermal runaway failure of lithium battery energy storage system will cause serious safety accidents, and lithium battery thermal runaway will precipitate various detectable gases through the safety gas valve. Effective monitoring of the precipitated gas can ensure the safe operation of the energy storage system. In this study, the adsorption behavior of CuO-GeS towards the main precipitated gases CO, CO2, CH4, and C2H4 in Lithium battery before thermal runaway is systematically studied based on DFT. The adsorption structure, DOS, DCD, and ELF are analyzed to explore the interactions between CuO-GeS monolayer and the gases. The results show that CuO-GeS monolayer achieves strong adsorption of CO and C2H4 and highly sensitive monitoring of CO2 and CH4. Furthermore, the relative molecular mass ratios of CxHy and CxHy-1F (x = 1, 2 y=2, 4, 6) gases to doped CuO can satisfy Smoothing Spline with adsorption energy and charge transfer, which can be used to estimate the adsorption properties of the homologous gases. The potential application of CuO-GeS monolayer in lithium battery energy storage systems lays a theoretical research foundation for the adsorption and detection of thermal runaway gas in lithium battery energy storage systems.

Control Optimization Method for Ship Direct Current Microgrid Based on Impedance Reshaping

In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First, a simplified small-signal diagram of a lithium battery energy storage system converter is analyzed. Combining active damping control technology, an impedance regulator is introduced, and its parameters are optimized to effectively reduce the output impedance magnitude on the power source side. Subsequently, a ship DC microgrid simulation model is constructed using MATLAB R2022a/Simulink for validation, and comparative analysis is conducted on the anti-interference ability of the DC bus voltage before and after impedance reshaping. Finally, a model is built on a semi-physical simulation platform to experimentally verify the proposed method. The research results indicate that the proposed control optimization method can effectively increase the system’s stability margin, suppress DC bus oscillations, and enhance the anti-interference ability of the ship DC microgrid’s bus voltage when facing significant power load variations.

Sulfur Solutions: Advancing High Voltage and High Energy Lithium Batteries with Organosulfur Electrolytes

AbstractAchieving energy densities exceeding 350 Wh kg−1 while operating at elevated voltages (>4.5 V vs Li/Li+) is attainable through judicious selection of electrochemical pairs at the cathode and anode. However, current state‐of‐the‐art electrolytes exhibit limited stability when exposed to systems operating at or above 4.3 V. This limitation contributes to the degradation of electrode materials and raises critical safety concerns, impeding the commercialization of such systems. Consequently, there has been a notable surge in research efforts aimed at developing innovative electrolyte compositions capable of supporting high‐voltage lithium‐ion batteries (LIBs). A substantial portion of this research has focused on the family of organosulfur molecules, which possess high oxidative stability. Organosulfur salts also facilitate the formation of dense, ionically conductive solid electrolyte interfaces (SEI) and demonstrate excellent solubility. This article provides a comprehensive overview of the field of organosulfur electrolyte components for their applications in energy storage, encompassing solvents, alternative conducting salts, and additives. It emphasizes the idea that the deliberate design of electrolyte compositions is instrumental in controlling electrode passivation, with organosulfur‐based structures historically proving advantageous in every aspect of the electrolyte. Crucially, it should be noted that many of these components are commercially available, holding significant implications for industrial applications.

Transfer operation ride though control strategy of the aircraft power supply system with lithium battery energy storage

The aircraft power supply system turns towards multi-source, and transfer operation will likely happen during flight missions and fault conditions. The transfer may lead to voltage interruptions and current surges, adversely affecting power quality. This paper proposes incorporating a lithium battery energy storage system (ESS) into the aircraft high-voltage direct current (HVDC) power system. The ESS employs a voltage control model with a lower voltage reference base, facilitating a smooth transfer operation during power interruptions. This approach reduces voltage fluctuations in the power supply system, enhances power quality, and enables seamless power transfer during the transfer operation.

A monitoring and early warning platform for energy storage systems based on big data analysis

This article focuses on the safe operation of lithium battery energy storage power stations and develops a data monitoring and safety warning platform for energy storage systems. The background, architecture, implementation methods, and main functions of the platform development are introduced in sequence. This platform significantly improves the safety of energy storage stations by implementing active safety monitoring and early warning, which is of great significance for the large-scale application and promotion of lithium battery energy storage stations.

The Study of High-Energy Lithium Polymer Cells for Second-Life Applications

The environmental impact of lithium-ion batteries (LiBs) depends directly on their useful lifetime. Doubling the useful lifetime cuts the environmental impact per functional unit in half. However, if the cell is insufficient for one application it can still be sufficient for another. The beneficial operational value of LiBs between various applications presents a prospective solution to environmental sustainability. However, the capacity and power of the LiBs tend to degrade over time, which is a major concern for its application. The investigation and identification of the several key battery aging mechanisms are essential to its second life application. This paper is focused on the experimental analysis performed on XALT 31 Ah high-energy lithium polymer cells with NMC 433 as active electrode material. Characterization and cycling tests were performed on new cells and the data obtained was compared to equal cells cycled 7 years ago. The tests were carried out with the same temperatures (25 and 45 degrees Celsius) for both new and old batteries, respectively. The internal resistance diminishes after 100 cycles for both new and old batteries at 25oC. It does however decrease more for the new batteries, than the old ones. The decrease in resistance can be due to an increase in capacity and it is normal to see in the BoL of a cell. In addition, the temperature during cycling is assumed to be higher than the storage temperature, which also can decrease internal resistance. Since both the new and old batteries behave the same way, it is argued that this is the natural development of resistance in this cell type. When cycled at 45oC, the cell resistance increased after 100 cycles. Even though resistance diminishes with increasing temperature. Other ageing mechanisms such as SEI growth and lithium plating are activated by higher temperatures, resulting in an increase in internal resistance at 45 degrees. For the new and old batteries, the dQdV curves at the BoL are very similar after 100 cycles, it is difficult to know if the trend would continue as the cells age further. Based on this study findings, new approaches can be developed for more accurate and reliable prediction on the aging degradation of high energy lithium batteries.

Great Challenges and New Paradigm of The In Situ Polymerization Technology Inside Lithium Batteries

AbstractIn situ polymerization technology is expected to empower the next generation high specific energy lithium batteries with high safety and excellent cycling performance. Nevertheless, the large‐scale commercial applications of most reported in situ polymer electrolytes are still full of challenges. Owing to the severe parasitic reactions caused by residual monomers, additional initiators and oligomers, lithium batteries using in situ polymer electrolytes often demonstrate limited specific capacity, poor cycling performance, and insufficient rate capability. However, this issue has not received adequate attention in previous reports. Furthermore, the design and evaluation of in situ polymer electrolytes still lack effective guidance and unified standards. Herein, the development history of in situ polymer electrolytes are systematically reviewed and critically disclose the great challenges. Then, from the aspects of monomers, initiators, separators, manufacturing technologies, safety and cycle life evaluation, unprecedentedly a new paradigm is provided for upgrading the in situ polymerization technology inside lithium batteries. It is hoped the novel paradigm will prompt much more insightful studies, expediting the commercialization of in situ polymerization technology in lithium batteries.

Design of Fuzzy Controller for Lithium Battery Formation LLC Converter Based on Sparrow Search Algorithm Optimization

This paper provides a novel fuzzy PI controller design for LLC resonant converters that make use of the sparrow search algorithm optimization. The LLC resonant converter is a complex nonlinear and time-varying system. As the trend in lithium battery energy conversion systems shifts toward high-power applications, they frequently encounter wide load variations. When employing traditional linear PI controllers of LLC resonant converters, the transient response is slow and fails to adapt effectively to the requirements of wide load changes. In this proposed approach, fuzzy control and PI control are combined to enhance the controller’s flexibility and transient response characteristics. The PI controller parameters are continuously adjusted online, incorporating fuzzy control outputs to improve the controller’s performance. Furthermore, the sparrow search algorithm is applied to optimize the proportional and quantization factors, minimizing the impact of improper parameter selection on the performance of the fuzzy PI controller. This method successfully addresses the challenges posed by the LLC resonant converter, improving adaptability and transient response characteristics in varying load conditions by combining fuzzy control and PI control, online parameter modification, and utilizing the sparrow search algorithm to optimize proportional and quantization factors.