Lithium iron phosphate (LiFePO₄) is one of the most widely used cathode materials in lithium-ion-based electric vehicles and energy storage batteries. To meet the market demand for high-energy-density lithium-ion batteries, high-energy-density LiFePO₄ products must be developed. According to the definition, energy density depends on the following three aspects: the voltage plateau, powder compacted density, and mass specific capacity. Based on electrochemistry and materials science, increasing the powder compacted density and mass specific capacity is a promising modification direction; however, voltage plateau is an intrinsic characteristic of LiFePO₄. Based on technical experience, market research reports, and previous research, the choice of raw materials, the modification of the sintering process, and particle gradation are the best modification methods for increasing powder compacted density. In the iron phosphate route, impurities are the primary issue in sintering processes; thus, different procedures for particle gradation are proposed. Considering mass specific capacity, the following strategies are proposed based on the intrinsic characteristics of LiFePO₄: nanosizing, carbon coating, elemental doping, defect control, and crystallographic preferred orientation. Moreover, nanosizing, carbon coating, and elemental doping are the most effective modification methods for increasing mass specific capacity. Usually, nanosizing and carbon coating are combined for increasing electronic conductivity, whereas elemental doping is mostly used for increasing Li-ion diffusion coefficient and preferred orientation. These modification methods are used in LiFePO₄ products available in the market and are confirmed by domestic battery factories. However, the energy density of LiFePO₄ has not yet been maximized; hence, additional methods for modifying the material properties and production processes need to be developed.

Lithium metal has extremely high specific capacity and very low redox electrode potential, which is one of the key energy materials in the field of secondary batteries. However, the metal lithium anode faces challenges such as volume expansion and uneven lithium deposition. Introducing a three-dimensional framework into the lithium metal anode to construct a composite lithium anode is an effective method to mitigate volume expansion and regulate lithium deposition. However, the composition and structure of composite lithium anode are very complex, the influencing factors of electrochemical reactions are strongly coupled with each other. With the advancements of physical and chemical models and significant improvements in computational capabilities, numerical modeling analysis has become a valuable tool to investigate the physical chemistry principles within composite lithium anodes. Firstly, the main process mechanisms of composite lithium metal anode and the development process of physicochemical models are summarized. Then quantitative models of the electrochemical mass transfer processes are introduced, including surface electric fields and ion fields in the composite lithium anode. And the progresses made in analyzing and controlling the dynamic evolution of lithium deposition morphology using phase field models or finite element models are overviewed. Finally, the structural stability of the composite lithium metal anode during the cycling process is analyzed from the perspective of the mechano-electrochemistry. These quantitative modeling efforts reveal the electrochemical principles of lithium anodes and drive the efficient screening and optimization design of composite lithium anodes.

The electrochemical and safety performance of lithium-ion batteries is closely related to the characteristics of their materials, electrodes, and cell levels. Revealing the multilevel failure mechanism of energy storage lithium-ion batteries can guide their design optimization and use control. Therefore, this study considers the widely used lithium-iron phosphate energy storage battery as an example to review common failure forms, failure mechanisms, and characterization analysis techniques from the perspectives of materials, electrodes, and cells. Multilevel failure in this article includes the structure, composition, and interface failure of anode and cathode materials; the failure of electrolytes and separators; the failure of lithium plating, porosity, exfoliation, and nonuniform polarization of electrodes; and the gas production and thermal runaway of cells. Finally, the future energy storage failure analysis technology is presented, including the application of advanced characterization technology and standardized failure analysis process to contribute to promoting the development of failure analysis technology for energy storage lithium-ion batteries.

This study investigated the effects of porosity, crack shape, and interface contact area of solid electrolyte (SE) on solid-state batteries (STFLIBs). We used the resistance network method to model the microstructure of SE and a one-dimensional electrochemical coupled contact area model for SLIB. We established a one-dimensional electrochemical and two-dimensional SE resistance network model based on this physical model and conducted electrochemical impedance spectroscopy (EIS) simulation analysis. By inputting different electrolyte properties into the battery model, we predicted the effect of microstructure on battery capacity and impedance. The results show that within the range of 0°～90°, smaller crack angles have less impact on the conductivity of SE. To compare the effect of crack shape on electrical conductivity more conveniently, we kept the crack area unchanged. As the crack length increases, the electrical conductivity loss gradually increases until it reaches the extreme point after which the electrical conductivity loss starts to decrease. When the dimensionless length of the crack is <0.25, the conductivity loss caused by triangular cracks is lower than that caused by rectangular and elliptical defects. However, when the dimensionless length is >0.25, the influence of triangular defects exceeds than that of rectangular and elliptical defects. With the increase of porosity, the conductivity of SE rapidly decreases in an approximately linear manner. Electrolyte defects lead to a decrease in the discharge voltage of the battery, which is reflected in the EIS simulation as an increase in bulk resistance. The loss of interface contact area has a more significant impact on the loss of battery capacity, and this impact is significantly lower at low discharge rates compared to high discharge rates. Under different contact areas ( γ= 1.0 and 0.4), the specific capacity decreases by 60.08%, while at high magnification (50 C), the specific capacity decreases by 81.95%. The impact of interfacial area loss is relatively small when the magnification is low. The loss of interface contact area results in an increase in charge transfer impedance. When γ changes from 1 to 0.2, the charge transfer impedance increases by 25 times, and the average charge transfer impedance increases by 118.60 Ω for each 0.1 loss of contact area. Compared to electrolyte defects, the impedance increase caused by interfacial contact area loss is more significant. In practical applications, the battery can ensure high capacity performance only when the interface contact area is greater than 0.7. This study simulated the electrolyte interface contact factors that lead to an increase in SLIB impedance, thereby enriching relevant research in this field.

With the rapid development of commercial lithium-ion batteries (LIBs), safety has become an increasingly prominent and urgent problem. As one of the important cases causing LIBs accidents, thermal runaway is closely related to the thermal stability of the solid electrolyte interface (SEI) on the graphite anode. Therefore, the properties of SEI must be deeply understood and accurately controlled to improve the safety of LIBs. Herein, the composition, structure, and formation principle of SEI are briefly introduced, and its key role in the processes of thermal runaway is emphasized. Second, the unsafe factors related to SEI and the mechanisms in the process of thermal runaway are discussed. We analyze the decomposition of SEI, the pyrolysis of lithiated graphite, the release of combustible gas, lithium plating, and the influence of transition metals on SEI. Our results indicate that the thermal stability and Li⁺ conductivity of SEI must be improved at the same time to effectively enhance the safety of LIBs. According to the decisive relationship between the structure and composition, properties, and properties of materials, researchers have conducted extensive research on the modification of SEI. The characteristics of SEI can be tuned by adjusting its electrolyte composition or introducing additives into the negative electrode to regulate the SEI insitu and constructing an artificial SEI with inorganic or organic components. Finally, we present the future research and regulation direction of SEI, which provides a theoretical basis and experimental guidance for improving the safety of LIBs.

Rapid development of portable devices, electric vehicles, and energy storage power stations has led to the increasing need of optimizing the cost, cycling life, charging time, and safety of lithium-ion batteries (LIBs). Gas generation during cycling and storage causes volume expansion and electrode/separator dislocation, which can increase electrochemical polarization and lead to decreased battery lifespan or safety hazards. Herein, we summarize the mechanisms with respect to the primary gases that evolve in LIBs, including oxygen, hydrogen, alkenes, alkanes, and carbon oxide, and describe the effect of operating temperature, voltage window, and electrode materials on gas generation. We also describe the relationship between this gas generation and LIB performance. We further propose several electrolyte-based strategies that focus on increasing the stability of the electrolyte and electrode/electrolyte interface. Specifically, the electrolyte stability is increased by employing functional additives to scavenge trace water, hydrofluoric acid, and active oxygen species, reducing the proportion of cyclic carbonates, and by using fluorinated solvents in the electrolyte. The adoption of film-forming additives can effectively improve the stability of the electrode/electrolyte interface, suppressing gas generation. In addition, we discuss the challenges and urgent issues related to gas generation in LIBs and provide unique perspectives on the intrinsic mechanism for developing increasingly efficient gas-suppression methods.

This study focuses on harnessing the advantages of prelithiation technology and prelithiation materials, also known as lithium supplements or prelithiation additives, by incorporating them into the positive electrode of lithium iron phosphate (LFP) batteries. Two battery prototypes were developed: A 51-Ah square aluminum-shell full battery with LFP and a 7-Ah soft-pack full battery. The cycle life of these batteries was tested and studied. Based on experience, the characteristics and impact on the battery life of main materials such as positive and negative electrodes (such as LFP, graphite, electrolyte ratio, current collector, and separator), auxiliary materials (positive and negative electrode adhesives, conductive agents, etc.), and prelithiation materials were analyzed. The lithium replenishment mechanism and lithium replenishment capacity of several prelithiation materials that have already been industrialized were analyzed through chemical reaction equations. Experimental results show that the cycle life of a 7 Ah battery with prelithiated materials reaches 9000 cycles, while a 7 Ah battery without prelithiated materials achieved 5300 cycles. The 7 Ah battery with prelithiated materials exhibits substantially better cycle performance compared to that without prelithiated materials, with a cycle life increase of over 50%. In terms of energy efficiency, the 7 Ah battery with prelithiated materials at 25 ℃ demonstrates an energy efficiency of 96.74% at 0.2 C, 94.80% at 0.5 C, and 92.67% at 1 C, surpassing the energy conversion efficiency of a 7 Ah battery without prelithiation materials. This research promotes the application of prelithiation technology and materials in long-cycle new energy storage LFP batteries. It provides an experimental basis and guidance for the design and development of long-life LFP batteries, thereby contributing to the advancement of energy storage systems.

Lithium-ion batteries have the advantages of high energy density, high working voltage, low self-discharge rate, and fast charging. They are widely used in various fields related to national defense industry and human life. After considerable efforts in developing the domestic battery industry, China has built a strong foundation in battery research and production. However, owing to the lack of battery computing models and design software, the design of novel batteries is still based on experience. Thus, relevant quantitative theoretical models and algorithm implementations are urgently needed. Lithium-ion battery systems have complex multiphysics coupling characteristics and multiscale characteristics in time and space. Unclear multifield coupling mechanisms related to lithiation and delithiation, the hard scale transitions in time and space, and the lack of design software are the main factors preventing the commercialization of novel materials in next-generation high-energy-density batteries. Herein, we propose a multiscale theoretical model and algorithm realization using the coupling of the electrochemomechanical behaviors of the batteries, including ① electrochemomechanical coupling theory of electrodes in lithium-ion batteries, ② finite element realization of multifield coupling behavior at various scales, ③ concurrent and hierarchical multiscale theoretical and numerical models of electrodes, and ④ electrochemomechanical behavior of the interface between the electrode and electrolyte.

This study aims to design a new liquid-cooling heat management system for lithium-ion battery packs. We have established a special experimental platform and a liquid-cooling system model coupled with an EV dynamic model to determine the optimal matching parameters for the components and the operational control strategies of the system. The results indicate that the deviation between experiment and simulation is within 3.0% under normal conditions. A higher flow rate and lower inlet temperature results in a lower battery temperature, while delaying the cooling intervention can reduce power consumption by around 20%. To further reduce the power consumption to 2750 W and maintain a battery temperature of 30.83 ℃ during normal 1.0 C discharge, we conducted a multiobjective optimization using the response surface method combined with genetic algorithm Ⅱ. Additionally, this optimization demonstrates a well-balanced solution between battery temperature and power consumption during the drive cycle. By combining the results of the experiment and simulation, this work provides valuable insights for designing an excellent liquid-cooling system for lithium-ion battery packs in electric vehicles.

Rechargeable lithium-ion batteries (LIBs) with high energy density have attracted considerable research attention as a power source for electric vehicles. However, charging at high rates causes the attenuation of battery capacity and power over time owing to lithium plating, mechanical degradation, and thermal effects. Reasonable design of electrode materials and electrolytes that facilitate the rapid transport of lithium ions is crucial for solving these issues. This paper reviews the current state of development related to the fast-charging technology with respect to LIBs. First, the physical and chemical basis of fast-charging LIBs is presented, which provides theoretical guidelines for achieving excellent fast-charging performance in LIBs. Second, the performance degradation mechanism of LIBs charged at high rates is introduced. Finally, the research strategies for achieving good fast-charging performance in high-energy-density LIBs are summarized from the perspectives of electrode materials and electrolytes. This paper provides guidance for designing fast-charging LIBs with excellent rate performance based on the systematic understanding and analysis of the latest advances.

Electrode coating is one of the key processes in the manufacturing of lithium-ion battery electrodes. The coating quality determines the uniformity of the electrode structure, which in turn affects the performance and lifespan of the battery. In response to the quality control problem of electrode slurry slot die coating, this study selects a local area composed of the slot die and the fluid collector as the research object and establishes a multiphysics field model coupled with phase field and flow field. Based on this model, the slurry flow during the slit coating process was analyzed through numerical simulation, providing a reference for optimizing the coating process parameters of lithium battery electrode slurry. Similarly, a stable coating window was determined based on the coating quality. The reliability of the simulation model was verified by comparing it with experimental results. We optimized the main dimensions of the coating die with the goal of expanding the coating window and achieving high-speed and stable coating. The results indicated that excessive or insufficient slurry flow rate will cause bubbles to mix in or overflow upstream, making the coating process unstable. The main geometric dimensions of the slot die had a specific impact on the stable coating window; however, simply increasing or decreasing the geometric dimensions cannot broaden the coating window. Asymmetric adjustment of the upstream and downstream die heads could increase the upper limit of slurry flow by 40% by changing the relative magnitude of upstream and downstream flow resistance.

According to the current industry research on the cycle characteristics of lithium battery modules, it has been determined that the main factor affecting the cycle performance of energy storage modules is the module expansion force. Through this study, the failure mechanism of the cycle attenuation characteristic of the energy storage module is identified. By improving the optimal design of the module structure, the increase in module expansion force can be greatly reduced, and the cycle life of the modules can be extended. Firstly, the causal and correlational relationships are accurately identified from the failure mechanism. Subsequently, a method is proposed to determine the foam size and bonding position between cells, enabling the optimization of the structural design of energy storage modules. Finally, a 1P8S energy storage module that uses a lithium iron phosphate 280 Ah cell was selected as the research object. A conventional energy storage module 1-1 was compared with an optimized energy storage module 2-1, both using the same 1P8S stack. The module cycle test was conducted under ambient temperature conditions of 25 ℃, employing a step charge of 0.5 C (140 A) discharge. The results show that the optimized energy storage module 2-1 exhibits improved performance in pressure and temperature differences at the end of charge and discharge compared to the conventional energy storage module 1-1. Specifically, the average pressure difference at the charging and discharging ends of the optimized energy storage module 2-1 is reduced by 24% and 37.7%, respectively. The average temperature difference of the optimized energy storage module 2-1 is reduced by about 5 ℃ and 6 ℃ at the charging and discharging ends, respectively. The capacity retention curve of the optimized energy storage module 2-1 is better than that of the conventional energy storage module 1-1.

Retired batteries must be resorted before echelon utilization, enabling them to meet the requirements of application scenarios for battery performance. The high cost of battery sorting for echelon utilization has become a technical bottleneck limiting its large-scale application. To reduce the cost of sorting and improving the technical and economic efficiency of battery echelon utilization, this study first studies the AC impedance characteristics of echelon-utilization batteries in different states, extracts characteristic frequency points to characterize battery states, and establishes a multifrequency point-based state of health (SOH) evaluation model for echelon utilization. Then, for developing a new model for echelon-utilization batteries, the model is optimized by testing the AC impedance and SOH data of a small number of samples. Finally, the open circuit voltage, multifrequency impedance, and estimated capacity were used as parameters for echelon-utilization battery sorting and compared with traditional sorting methods. The experimental results show that the maximum error of the optimized model in evaluating the SOH of the new battery model is within 3% and the MAPE is 1.93%, i.e., there is a significant reduction in the evaluation error compared to the unoptimized model. The cycling performance of battery pack sorting using this method is very close to that of traditional methods, which verifies the effectiveness of this sorting method. Moreover, this method can considerably shorten the sorting time of echelon-utilization batteries and has good engineering application value.

With the rapid development of electric vehicles, ensuring the health and performance evaluation of large-scale battery systems has become a crucial technological challenge. This paper focuses on addressing this issue by constructing an equivalent circuit model for battery packs. The health status of multiple battery packs is simulated using a combination of orthogonal parameters, representing different types of inconsistencies. Additionally, a dataset of battery pack samples is generated through model simulations. To classify the battery packs efficiently, a convolutional neural network (CNN) model is established. This model extracts morphological features from the local charging voltage curve images of the battery packs. These features serve as input for the CNN, enabling quick classification. Four parameters, namely available capacity, available energy, capacity utilization rate, and energy utilization rate, are selected for evaluation. The weight of each parameter is determined using the Analytic Hierarchy Process. Consequently, a comprehensive health evaluation index is proposed, which takes into account various performance characteristics of battery packs. This index facilitates the screening of battery components based on their evaluation scores. The classification model is trained and tested using the simulated dataset, yielding promising results. The constructed battery pack classification model achieves an accuracy of over 97% on the test set. The effectiveness of this method is further validated by evaluating the model with various indexes, such as the confusion matrix for classification tasks. Overall, the proposed method, which involves the visual feature extraction-based comprehensive assessment and screening of battery pack health status, contributes to the advancement of battery performance evaluation research. It also provides a new theoretical foundation for the health supervision of battery systems.

Accurately predicting the remaining useful life (RUL) of lithium batteries can ensure timely understanding of the internal performance degradation of the battery, reduce the risks associated with battery use, and provide a reliable theoretical basis for routine maintenance. To improve the accuracy and stability of prediction results, a lithium-battery RUL prediction model based on the combination of ensemble empirical mode decomposition (EEMD) and gated recurrent unit (GRU) with multiple linear regression (MLR) is proposed. First, the model decomposes the lithium-battery capacity data into several high-frequency and low-frequency components using the EEMD algorithm to reduce noise interference in the capacity data. Then, based on the characteristics of each component, the model builds prediction submodels based on the obtained high-frequency and low-frequency sequences using the GRU and MLR networks, respectively. Finally, the predicted values of each submodel are superimposed and fused to obtain the RUL of the battery based on the public data on lithium batteries provided by NASA and Oxford; furthermore, using different prediction starting points, the obtained results are compared with those of other single and combined models. The experimental results show that the EEMD-GRU-MLR prediction model can provide accurate RUL results, compared with LSTM, GRU, and EEMD-GRU prediction models, with the maximum mean absolute error decreased by 0.0311, 0.0234, and 0.0182, respectively, and the maximum root mean square error decreased by 0.0235, 0.0153, and 0.0098, respectively, This proves the satisfactory ability of the proposed EEMD-GRU-MLR model to predict the RUL of lithium batteries.

Accurate estimation of the state of charge (SOC) of lithium-ion batteries under a wide range of operating conditions is crucial for ensuring the operational safety and reliability of electric vehicles; therefore, estimating SOC is one of the most important tasks of battery management systems. In this study, a fusion neural network model combining Self-Attention Mechanism (SAM) and Gated Recurrent Unit (GRU) is proposed to capture the long-term nonlinear mapping relationship between the measurable parameters (voltage and current) and SOC of lithium-ion batteries. This SAM-GRU neural network model makes full use of the short-time processing capability of GRU and the long-time sequence feature-extraction capability of SAM. Additionally, this model simplifies the effective characterization of the long-sequence-related features of SOC. Based on the results of the Beijing Bus Dynamic Stress Test, the proposed SAM-GRU neural network model yields more accurate SOC estimates than the traditional GRU neural network under different discharge rates, environmental temperatures, and combinations of both. Specifically, the improvements in accuracy are no less than 26%, 25%, and 11%, respectively.

Accurately predicting the degradation of lithium-ion battery life is crucial to ensure the safe and reliable operation of electric vehicles and electrochemical energy storage systems. However, predicting the life of lithium-ion batteries under various operating conditions remains a major challenge. This article presents a novel approach to construct feature matrices and predict battery life using deep convolutional neural networks. First, battery life degradation is defined in terms of capacity decay. A multidimensional feature parametric matrix is then built based on the dataset's characteristics, including variable operating conditions. This matrix combines historical capacity information, cycle count information, and operating conditions information. Next, a one-step ahead mapping relationship is established using the feature parameter matrix as input and the battery capacity to be predicted as output. To achieve this mapping relationship, a deep learning method with strong nonlinear capability is employed. It builds a dilated residual regression network by combining a dilated convolution module, a residual module, and a regression module. Furthermore, Bayesian Optimization is used to train the proposed network and find the best combination of hyperparameters, ensuring the model's optimality. Experimental results demonstrate that the proposed method significantly enhances prediction accuracy compared to commonly used model- and data-driven methods for the battery life prediction. Moreover, the proposed method exhibits robust prediction capability across different prediction starting points.

In recent years, energy storage technology has been developing rapidly; thermal safety issues have been one of the elements limiting its large-scale promotion. Liquid-cooled LiFePO₄ modules have been widely used owing to their excellent electrochemical performance and thermal management features. However, they still cannot eliminate thermal runaway misfires caused by abuse and need the support of early warning technology to guarantee the normal operation of energy storage systems. In this study, we use an embedded air-pressure sensor and the thermal management system of a liquid-cooled module of LiFePO₄ battery to detect the sudden change of air pressure caused by the opening of the battery safety valve in real time and realize the early warning of the thermal runaway of a liquid-cooled module. The experimental platform for the liquid-cooled module thermal runaway and Fluent fluid simulation platform is built to study the thermal runaway phenomenon of single-cell overcharge in a liquid-cooled module, verify the effectiveness of early warning, and analyze the fluctuation and distribution characteristics of air-pressure signal in the module with the development of the internal degradation of the battery during the overcharge process. The results show that when the liquid-cooled module with a volume of 0.18 m3 is overcharged with a 1 C multiplier on a 13 Ah LiFePO₄ single-cell battery, a sudden change of 200 Pa occurs when the battery safety valve opens, the battery temperature reaches the highest after an average of ～304 s, and a complete thermal runaway occurs. To further optimize the selection and arrangement of the barometric pressure sensor, the barometric pressure signal at each position on the front panel of the liquid-cooled module is studied. To further optimize the selection and arrangement of the air-pressure sensor, the specific changes of the air-pressure signal at each position on the front panel of the liquid-cooled module are studied, and the suitable selection range and the best installation position of the acquisition frequency of the air-pressure sensor and other parameters were obtained. The results provide theoretical and data support for the application and safety protection of air-pressure sensors in liquid-cooled modules.

In this study, the gas-composition and ignition characteristics of thermal runaway fires in full-sized electric-vehicle lithium-ion battery systems are investigated. A full-sized electric-vehicle fire-test platform is built, and a gas collection device is designed. The toxic gas composition and ignition characteristics are measured using Fourier transform infrared spectroscopy and an explosion-limit test instrument. The gas release process during an electric vehicle fire is analyzed, and the gas release in the battery compartment is divided into four stages according to the thermal runaway characteristics. The gas-composition characteristics in these four stages are analyzed. In the first stage, electrolyte vapor is primarily released, whereas in the second stage, hydrogen is mainly released. A large amount of sulfur dioxide gas is released in the third stage, with the concentration reaching 10906.4 ppm, and the mechanism of sulfur dioxide generation is analyzed. Hydrogen cyanide gas is produced in the early stages of combustion in a cockpit, with a maximum concentration of 120.4 ppm. The main sources of various toxic gases in the cockpit are analyzed. The explosion limits of the gases in the battery compartment in different stages are measured. The explosion limits of the gases released from the battery compartment range from 4.83% to 73.77%. The explosion hazards calculated for each stage indicate that the second stage of thermal runaway in the battery compartment has the highest explosion hazard. The analysis of variations in explosion characteristics of the gas mixture released from the battery compartment suggests that the inert gas content mainly affects the lower explosion limit of the mixtures, whereas hydrogen content mainly affects the upper explosion limit of the mixture.

To study the types and safety of thermal runaway gas released by lithium-ion batteries in an aviation transformer environment, an independent closed-type transformer laboratory was constructed for conducting related experiments. The thermal runaway characteristics of terrapin lithium-ion batteries with 100% state of charge were investigated under different pressure environments (101, 70, and 30 kPa). The temperatures of the lithium batteries during thermal runaway and the pressure changes within the closed laboratory chamber were recorded to compare the thermal runaway characteristics under varying pressure conditions. The resulting thermal runaway gas was analyzed using a gas chromatograph-mass spectrometer, and an independent explosion limit test platform for lithium batteries was developed. Composition analysis and explosion risk analysis were performed to assess the thermal runaway gas produced by lithium batteries. The findings indicate that as the ambient pressure decreases, thermal runaway is triggered earlier; however, the risk of high temperature and gas shock is reduced. Additionally, the composition and content of gases produced vary with different pressure environments. As environmental pressure decreases, the content of CO₂ decreases, while the content of unsaturated hydrocarbons such as C₄H₈, C₄H₆, and C₅H₁₀ increases. This is also the reason for the greater risk of explosion in low-pressure environments. The range of thermal runaway gas explosion for lithium-ion batteries expands with decreasing pressure, resulting in a greater risk. These research results provide a theoretical basis for the safety research of lithium-ion batteries in aviation and offer data references for the safety prevention and control of lithium batteries.

The safety and reliability of a vehicle depend on the consistency of the safety characteristic parameters of its power battery system. To analyze the threshold and causes of these parameters throughout the lifespan of the battery, this study conducts the cloud data analysis and high/low temperature charging and discharging test on retired battery systems, as well as the extreme condition test on battery cells. The maximum differences in voltage and temperature serve as indicators to evaluate parameter thresholds. The results show that the voltage difference threshold of a vehicle gradually increases with the service time. The main reason for a large voltage difference is the high discharging current during the driving process. Owing to the low state of charge, the experimental voltage difference is larger compared to the difference in voltage obtained from cloud data. The temperature difference threshold of the battery system is closely related to the ambient temperature. Although the maximum temperature difference does not appear during a single charging-discharging process in low-temperature conditions, the continuous driving or charging process in winter can increase temperature difference. After the overtemperature test of new and degraded batteries, the open circuit voltage of the degraded battery was directly reduced to 0 V, and its internal resistance and thickness increased substantially, indicating that the safety performance of a degraded battery deteriorated under extreme conditions. With the testing and analysis results of safety characteristic parameters under different conditions, this study contributes to the consistency analysis and the development of warning strategies for power battery systems.

In this study, research progress on safety assessment technologies of lithium-ion battery energy storage is reviewed. The status of standards related to the safety assessment of lithium-ion battery energy storage is elucidated, and research progress on safety assessment theories of lithium-ion battery energy storage is summarized in terms of battery intrinsic safety, energy storage failure and accident statistics, thermal runaway mechanism, and fire spread mechanism. Numerical simulations and safety assessment technologies from lithium-ion battery cells to energy storage systems are analyzed, and the current situation of the safety assessment technology of energy storage power stations is introduced. The results indicate that, with the continuous iteration of battery technology and the continuous upgrading of energy storage system structures, the safety assessment of energy storage becomes more and more complex; thus, existing assessment techniques and standards must be further improved. In the future, safety assessment indexes must be adjusted and updated according to the development of energy storage battery intrinsic safety and electrical and fire safety technologies. By combining the progress of simulation and experimental means, safety index thresholds are clarified, as well as the evolution of safety performance accompanying capacity decay and aging after the energy storage system is put into operation. This study aims to build a safety performance level assessment system covering multiple systems, scenarios, and elements; integrate dynamic and static indicators; and develop a safety performance rating assessment technology for energy storage systems that covers "cell-module-unit-system-power plant" layers. Finally, we aim to develop an internationally applicable safety performance assessment standard for energy storage systems and provide Chinese solutions for global energy storage safety.

Lithium-ion batteries are complex systems containing multiscale and multiphysical fields. Electrochemical simulations can describe the chemical and physical processes in batteries, providing theoretical support for the optimization of battery systems and their design to reduce the time and costs related to battery development. This article summarizes electrochemical models and their derived models, including single-particle, pseudo-two-dimensional, three-dimensional, and mesoscale models. This study also introduces several parameter acquisition methods. Additionally, the applications of electrochemical models in internal temperature and stress analysis, aging simulation, and microstructure design of lithium-ion batteries are summarized. Based on electrochemical models, the distributions of lithium ions, potential, and reaction rate in battery electrolyte and electrodes are studied. Furthermore, an electrochemical model coupled with multiphysical fields is introduced to simulate the temperature and stress distributions in cells and predict the degradation of cells during cycling. The effects of microstructure and various parameters on battery performance are investigated using the microcosmic electrochemical model to guide electrode structure design. In summary, electrochemical models have great advantages for analyzing the internal mechanisms of batteries. Finally, directions for future research on electrochemical models for lithium-ion batteries are suggested.

With the vigorous development of the new energy industry in recent years, power batteries will usher in a large-scale retirement tide. Echelon utilization of power batteries can not only maximize the value of batteries and reduce the life cycle cost of power batteries but also weaken the threat of retired power batteries to the environment and alleviate the problems of high cost and low income associated with traditional energy storage systems. The traditional screening technology for consistency in the capacity division and constant capacity has low efficiency and high cost, making it difficult to adapt to the screening needs of power battery consistency in multiple scenarios. Data analysis has yet to play an integral role in the screening process; thus, fast and efficient battery screening technology has become one of the critical technologies for the large-scale application of retired batteries. Additionally, the existing echelon utilization technology cannot solve the problems of poor consistency; moreover, the degradation of the reorganized battery cascade operation is fast and the aging pattern is difficult to predict, posing significant safety hazards. The echelon utilization of retired power batteries still needs to achieve breakthroughs associated with large-scale applications, such as consistency management, dynamic safety monitoring, and regulation. Although the demonstration application of echelon utilization battery energy storage systems achieved satisfactory results initially, it still faces technical challenges such as system safety and economy. This study summarizes the research status of key technologies, such as sorting, evaluation, screening, detection, recombination, balancing, and safety of retired power batteries, by exploring recent relevant literature. It characterizes the industrial policies and national industry standards related to the echelon utilization of retired power batteries, which is expected to provide a reference for the reasonable use of large-scale retired power batteries.

This bimonthly review paper highlights a comprehensive overview of the latest research on lithium batteries. A total of 3612 online studies from April 1, 2023, to May 31, 2023, were examined through the Web of Science database, and 100 studies were selected for highlighting in this review. The selected studies cover various aspects of lithium batteries, focusing on cathode materials such as LiNi_0.5Mn_1.5O₄ and LiCoO₂. Investigations into the effects of doping and interface modifications on their electrochemical performances and structural evolution during prolonged cycling are discussed. For alloying mechanisms in anode materials, such as silicon-based composite materials, many researchers emphasize material preparation, optimization of electrode structures to buffer volume changes, and the application of functional binders and interface modification. Great efforts have been devoted to designing three-dimensional electrode structures, interface modifications, and controlling the inhomogeneous plating of lithium metal anode. Studies on solid-state electrolytes focus on the structure design and performances in sulfide-based, chloride-based, and polymer-based solid-state electrolytes and their composites. In contrast, liquid electrolytes are improved through optimal solvent and lithium salt design for different battery applications and incorporating novel functional additives. For solid-state batteries, studies mainly investigate the compatibility of layered oxide cathode materials with sulfide-based and oxide-based solid-state electrolytes. To address the challenges in Li-S batteries, composite sulfur cathode with high ion/electron conductive matrix and functional binders are explored to suppress the "shuttle effect" and activate sulfur. Additionally, this review presents work related to dry electrode coating technology, characterization techniques of lithium-ion transport in the cathode, lithium deposition, and theoretical calculations to understand electrolyte viscosity and the solid-state electrolyte/cathode interface. This review provides valuable insights into the advancements in lithium batteries, contributing to the overall understanding and progress in the field.

New energy construction projects typically face may issues, such as single energy supply, simple electricity management, harsh operating environments, and difficult operations. Therefore, this article mainly proposes different solutions for various extreme operating environments, such as high altitudes, extreme cold conditions, islands, and deserts. Liquid-cooled energy storage system solution is proposed to address the issues of imbalanced electricity, large temperature differences between battery cells, and low energy densities in traditional air-cooled energy storage systems. This article proposes solutions for new energy construction projects in extreme operating environments, and can provide constructive suggestions for the design and operation of related projects.