This bimonthly review paper highlights 100 recent published papers on lithium batteries. We searched the Web of Science and found 3084 papers online from Dec. 1, 2022 to Jan. 31, 2023. 100 of them were selected to be highlighted. High-nickel ternary layered oxides, LiNiO₂ and LiNi_0.5Mn_1.5O₄ as cathode materials are included in the investigations for doping and surface coating to stabilize crystal structural and suppress interface side reactions. For anode, investigations mainly focus on Si-based anode, lithium metal and anode-free technology. Meanwhile, the surface coating, interface construction and binder design draw much interest to relieve the volume expansion of Si-based anode. The interface engineering of Li metal and anode-free collector has been widely studied. Researches for solid state electrolyte including sulfide, polymer and composite electrolyte, emphasize the synthesis process, electrolyte film preparation and electrolyte-electrode interface construction. While large efforts are still devoted to liquid electrolytes for the electrolyte-electrode interface design and regulation using additives. For solid-state batteries, there are a few papers related to the surface coating, design of composite cathode and inhibition of Li dendrite and side reactions. Other relevant works are also presented to the cathode design of lithium sulfur battery. The characterization techniques are focused on chemical component measurement, battery failure analysis, lithium deposition behavior and SEI. Theoretical simulations are directed to battery performance prediction and electrolyte design. The interfaces of electrolyte/electrodes are also drawn large attentions.

Herein, the molecular dynamics method investigates the effects of Al₂O₃ nanoparticles on the structure and thermophysical properties of binary chloride salt LiCl-KCl. Furthermore, the effect of doping amount and temperature on radial distribution function, coordination number [N(r)], self-diffusion coefficient(D), density, viscosity, and thermal conductivity of nanofluids were analyzed. The results show that in the temperature range of 700～1400 K, with increasing nanoparticles, the first peak position of the radial distribution function g_Li-Cl(r) moves to the left gradually, the peak height and the coordination number increase, and the self-diffusion coefficient decreases gradually. The density, viscosity, and thermal conductivity of nanofluids decreased with increasing temperature but increased with increasing nanoparticles, and the maximum viscosity and thermal conductivity increased by 16.83% and 4.95%, respectively. The change in thermophysical properties was attributed to adding Al₂O₃ nanoparticles that reduced the distance between anions in the nanofluids, enhancing the association effect, and making the melt structure more compact.

Paraffin/GO (graphene oxide) composite phase change materials are prepared and characterized for latent heat, thermal conductivity, and fluidity to increase the energy efficiency of solar PV/T (photovoltaic/thermal) systems. With a phase change temperature of 35 ℃, a latent heat of phase change of 42.93 J/g, a maximum thermal conductivity of 0.505 W/(m·K), and a viscosity-temperature fit of 0.91, the composite phase change material with a GO mass fraction of 0.02% has the best overall performance when compared to other known composite phase change materials. Two identical flat-plate heat pipe solar PV/T systems are built, and paraffin/GO composite phase change materials (a GO mass fraction of 0.02% and water) are operated as the heat transfer medium for both systems to analyze the effect of the paraffin/GO composite phase change material on the thermoelectric performance of a solar PV/T system. Herein, characterization of the thermoelectric performance of the solar PV/T system using thermal and electrical efficiencies was performed. Results show that under the same operating conditions, the thermoelectric performance of the flat-plate heat pipe solar PV/T system running (paraffin wax mass fraction of 30% and GO mass fraction of 0.02%) with a paraffin/GO composite phase change material is improved compared to that running with water, with an increase in system thermal efficiency of 92.28%, electrical efficiency of 8.87%, and heat collection in the heat exchanger tank of 15.80%. This study provides value for applying composite phase change materials (fluids) in solar energy storage.

Large capacity power flywheel energy storage system is the high-quality frequency modulation resource of the power system. The primary technique for enhancing flywheel energy storage is the use of high-strength and low-density composite material to create flywheel rotors. In this study, the large-size composite flywheel rotor is taken as the object. Based on the elastic theory, the stress distribution formula of the anisotropic material rotor rim under high-speed rotation is obtained. The interference fit between the composite rim and the metal hub's stress analysis formula is obtained based on the principle of stress superposition, and an analytical solution is provided. Then the finite element analysis model of interference fit between the composite rim and metal hub is established, and the stress distribution of the rotor is simulated and analyzed. The simulation results are consistent with the analytical results, which confirm the rationality of the model. Finally, the impact of interference on the stress of the contact surface between the metal hub and the composite rotor rim as well as the impact of the flywheel rotor's deformation at a specific speed are investigated.

The structure of the filling material in the packed bed has an important impact on the flow and heat storage and release performance in the packed bed. In this study, a kind of packing material with cube cell structure is designed, which can be stacked orderly and stably, making the fluid flow and heat transfer in the packed bed more uniform. Through numerical simulation, the planned cube cell's heat transfer and flow characteristics were examined. The convective heat transfer and pressure loss in the cube cell under different mass flow rates were examined. The outcomes were contrasted and examined using both the conventional spherical simple cubic packing structure (SC) and the body-centered cubic packing structure (BCC). The results demonstrate that when the mass flow rate is less than 0.0018 kg/s, the heat transfer coefficient of the cube cell is slightly lower than BCC, but considerably higher than SC; When the mass flow rate is larger than 0.0018 kg/s, the heat transfer coefficient of the cube cell increases rapidly, which is significantly higher than that of BCC and SC; With the increase of mass flow rate, its heat storage/release rate is gradually higher than that of BCC and SC. Fluid in the cubic cell experiences pressure drops that are always between SC and BCC, but they rise quickly when the fluid mass flow rate rises. By examining the comprehensive heat transfer performance, it is discovered that the comprehensive heat transfer performance of cube unit is obviously better than that of BCC, and its comprehensive heat transfer performance is the best when the mass flow rate is less than 0.0018 kg/s. A reference for the filler structure of a neatly packed bed, the entire research demonstrates that the cube cell created in this work has more complete benefits in both heat transfer speed and flow pressure drop.

Lithium-ion batteries are favored in developing new energy vehicles with good performance. However, due to the inconsistency of batteries and other reasons, some batteries become overcharged, and the long-term change cycle will affect their performance and life. This study conducted overcharge cycle tests of 4.3, 4.4, and 4.5 V for lithium-ion batteries. Entropy coefficient, direct current resistance, heat generation power, and heat generation of the battery were obtained by conducting an open-circuit voltage temperature coefficient test, a hybrid pulse power characteristic test, and an isothermal calorimetry test on a new battery and that after an overcharge cycle. The battery's reversible and irreversible heat were calculated using the Bernadi heat generation model. The overcharge cycle's influence on the battery's heat generation characteristic was analyzed comprehensively. Results show that a high overcharge voltage has a more noticeable impact on battery performance. Compared with the new battery, the direct current resistance of that after 4.3 and 4.4 V overcharge cycles did not increase significantly. However, the maximum internal resistance of the battery rose by 42.41% after 4.5 V overcharge cycles. After the overcharge cycle, the entropy coefficient curve of the battery fluctuates even more, and the amplitude increases with an increase in the cycle voltage. Compared with the discharge cycle, the overcharge cycle more obviously influences heat generation when charging. It first affects the reversible heat in the battery's heat source. An increase in overcharge voltage causes the proportion of reversible heat to increase.

Based on the high theoretical lithium storage capacity of molybdenum disulfide (MoS₂) and the good conductivity of graphene, a curly lamellar MoS₂/reduced graphene oxide (RGO) composite was successfully prepared by a one-step hydrothermal method. The structure, morphology, and composition of the MoS₂/RGO composite were characterized using an X-ray diffractometer, scanning electron microscope, X-ray energy spectrometer, and Raman spectrometer. The most stable adsorption position of lithium-ion, charge density, charge density difference, density of states, and diffusion energy barrier of MoS₂ and MoS₂/RGO models were calculated by first-principles. Results show that the MoS₂/RGO composite maintains a high discharge specific capacity of more than 800 mAh/g in the first 70 charge and discharge cycles. After 100 cycles, the discharge specific capacity of the MoS₂/RGO composite is 515.3 mAh/g, which is significantly higher than that of MoS₂ (170.8 mAh/g). Simultaneously, the composite material shows a better rate of performance than MoS₂. When the current density is back to 100 mA/g after the 1000 mA/g high current density cycle, the MoS₂/RGO composite still maintains a high discharge specific capacity (941.2 mAh/g). The first-principles calculation results show that the charge near the Mo atom of MoS₂ decreases, and the whole density of states of the MoS₂/RGO composite is enhanced due to the action of graphene, making it easier for electrons in the valence band to migrate to the conduction band. Furthermore, compared with MoS₂, the low diffusion energy barrier (0.25 eV) of MoS₂/RGO makes it easier for lithium ions to diffuse. Therefore, it explains why the MoS₂/RGO composite has a better electrochemical performance than MoS₂ with the effect of graphene.

In this study, Fe³⁺ was used to modify the graphene oxide (GO) free-standing film containing GO pre-encapsulated Fe₃O₄ to prepare Fe³⁺ crosslinked with reduced graphene oxides free-standing film by pre-encapsulated Fe₃O₄ nanospheres (Fe^3+?@Fe₃O₄/rGO). Scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy (XPS), and other test techniques were used to characterize the composition, structure, and morphology, and to study Fe^3+?@Fe₃O₄/rGO free-standing film lithium storage performance as the cathode of lithium-ion batteries. The results reveal that spherical Fe₃O₄ nanoparticle are tightly wrapped by GO layers, and the stability of Fe³⁺@Fe₃O₄/rGO free-standing film crosslinked by Fe³⁺ is significantly improved. The electrochemical results demonstrate that after 100 cycles of constant current charge and discharge with a current density of 100 mA/g, the specific discharge capacity of Fe³⁺@Fe₃O₄/rGO is 545 mAh/g, which is considerably higher than that of Fe₃O₄/rGO free-standing film discharge ratio capacity of 452 mAh/g before Fe³⁺ crosslinking, which proves that the free-standing composite structure after Fe³⁺ crosslinking shows outstanding electrochemical cycle stability. Additionally, the quick and easy procedure for creating cation-induced GO free-standing film can be used to additional active electrode materials.

Recently, with the large-scale application of renewable energy, the development of safe and reliable energy storage equipment is essential to solving the intermittent and unstable problems of renewable energy and realizing sustainable energy output. Lithium-ion batteries (LIBs) are an important energy storage device in many fields. However, future application requirements are challenging due to limited reserves, uneven distribution, and the high cost of lithium resources. Hence, interest in sodium-ion batteries (SIBs) arises for storing energy similarly to LIBs since sodium and lithium are in the same main group. Besides similar physical and chemical properties, SIBs also have great storage capacity and cost advantages. Developing anode materials with high capacity, excellent rate performance, and long cycle life is the key to the industrialization of SIBs. Carbon-based anode materials synthesized from abundant, low-cost, and renewable biomass have been widely studied. Their excellent sodium storage performance has been proven, which is expected to become the most promising novel low-cost and high-performance anode materials for SIBs. This study discusses biomass-derived carbon-based materials derived from plant organs, straw, and waste biomass. The methods of producing biomass-derived carbon-based anode materials by pyrolysis, chemical activation, and template methods are described. The sodium storage properties and mechanism of biomass-derived carbon-based materials with different structures are discussed. Finally, the future research direction of biomass-derived carbon-based anode materials is forecasted.

High-entropy oxides, a new class of single-phase solid solution materials, have recently attracted significant attention as conversion-type anode material for lithium-ion batteries (LIBs). Prelithiated Li _x (Mg, Ni, Zn, Cu, Co)_1-x O (x=0, 0.08, 0.16, 0.2) high-entropy oxide anode materials are synthesized by a chemical reaction of LiH with metal oxides, and the electrochemical performance of the prepared high-entropy oxides are investigated in this study. Introduction of low-valence Li⁺ in the lattice and charge compensation effect facilitate the formation of Co³⁺, Ni³⁺ and oxygen vacancies. Existence of high-valence Co³⁺ and Ni³⁺ increases the electron transfer number of the conversion reaction. The oxygen vacancies promote the electron/ion transportation of the oxide electrode and improve the conversion reaction kinetics. Meanwhile, the inactive Mg²⁺ makes the high entropy oxides maintain the stable rock salt structure upon lithiation/delithiation, which ensures the structural stability during the electrochemical process. As a result, a high reversible specific capacity (679 mAh/g at 100 mA/g), an improved first Coulomb efficiency (63.7%), a decreased polarization (voltage discrepancy between charge and discharge plateaus of -0.9 V), a good cycling stability and high rate capability (reversible specific capacity of 651 mAh/g after 800 cycles at 1000 mA/g) are achieved for prelithiated Li_0.16(Mg, Ni, Zn, Cu, Co)_0.84O high-entropy oxide anode material.

Due to its favorable operating voltage and affordable fabrication, MnO₂ cathode for AZIBs has garnered considerable interest. However, the development of rechargeable Zn//MnO₂ batteries is severely restricted by the limited specific capacity and poor cycling stability arising from the inherently poor electrical conductivity and structural collapse of MnO₂ cathodes during the charge-discharge process. The common methods for increasing the conductivity and cycling stability of the MnO₂ cathode are discussed in this review through the use of related literature research and analysis. The relationship between the crystal structure of MnO₂ and the specific capacity of the battery was established by examining the electrochemical performance of various structures of MnO₂. Meanwhile, the effect of different synthesis methods on MnO₂ shapes was also summarized for MnO₂ synthesis in the future. Furthermore, a brief discussion of the improvement in conductivity and cycling stability of the MnO₂ cathode brought on by the addition of other elements to the MnO₂ lattice and carbon-based materials is provided. Finally, the future development of MnO₂ cathodes with high performance is investigated. The various enhancement strategies can be synergistically adopted to improve the electrochemical performance of the MnO₂ cathode.

In this study, K⁺ incorporated into δ-MnO₂ (K-δ-MnO₂) are prepared by a facile redox method and applied as cathodes in aqueous zinc ion batteries (AZIBs). The pre-intercalated K⁺ acting as structure stabilizing "pillars" allows the tune of the lattice space of MnO₂ and promotes the diffusion kinetics of Zn²⁺ in the tunnel structure. Additionally, cations introduce shallow donor levels that enhance hosts' electronic conductivity and activate additional active sites. Besides, the co-intercalating water screens the intercalation between the intercalated Zn ions and the MnO₂ cathode, resulting in faster intercalation processes. The as-prepared K-δ-MnO₂ as cathode materials for AZIBs shows a relatively high capacity (401.3 mAh/g at 0.3 A/g) and an impressive cycling stability (83.2% retention after 1200 cycles at 3 A/g), while an inferior cyclability is observed for the pristine δ-MnO₂. The energy storage mechanism is clarified as H⁺/Zn²⁺ coinsertion/extraction via an ex-situ XRD characterization. With the combination of CNT, the composite electrode of K-?δ?-MnO₂/CNT displays better cycling stability (98.6% retention after 1200 cycles at 3 A/g). The K-δ-MnO₂ prepared by the facile redox method, which is simple and easy upscaling from the laboratory to industry, shows great potential as the cathode for AZIBs with good electrochemical performance.

Developing advanced lithium-ion batteries requires high-performance battery materials or optimized battery structures. An in-depth understanding of the aging degradation mechanism of battery materials is a prerequisite for improving battery performance. The in-situ optical microscopy method has advantages of convenient operation, a realistic simulation environment in in-situ reaction cells, and characterization from mesoscopic to macroscopic scales. This paper reviews the recent progress in the in-situ study of the aging degradation of lithium-ion battery materials via optical microscopy. Furthermore, typical structures of in-situ optical microscopy reaction cells are summarized. Then, several applications are reviewed, including lithium-ion concentration and its distribution, lithium plating, volume expansion and cracking of battery materials, and stress-strain evolution. Finally, future directions on optical microscope resolution, the functionality of in-situ reaction cells, the combined use of different characterization methods, and advanced image processing and analysis methods are proposed.

When lithium-ion battery operates at low temperature, their electrochemical performance cannot reach the optimal state, and their capacity deteriorates rapidly, which limits their application in extremely cold regions, aviation, national defense and military, and other fields. Therefore, improving the low-temperature performance of batteries has become an interesting field of research, and this study discusses the relevant strategies in the literature. The effects and mechanism of factors, including new lithium salts with high conductivity, mixed solvents with low melting point and high dielectric constant, and film-forming additives that facilitate stable solid electrolyte interface (SEI) films, on the low-temperature performance of lithium-ion batteries, are emphatically studied. The comprehensive analysis shows that the solvation structure of Li⁺ and the behavior of the desolvation at the electrode interface directly determine the low-temperature performance of the battery. The importance of designing low-temperature electrolytes using the solvation structure of electrolytes was emphasized. It provides a novel idea for developing low-temperature lithium-ion batteries in the future.

Dicationic ionic liquids (DILs) have attracted extensive attention from researchers in various fields due to their extremely high chemical stability, electrochemical stability, thermal stability, and environmental friendliness. Based on the structural characteristics of DILs, the effects of different anions, cations, and link chains on the physicochemical properties of DILs are reviewed, and also some typical synthesis pathways are summarized. In this paper, the research status of DILs in electrolyte systems of different energy storage and conversion devices is summarized and analyzed. When used in the electrolyte of lithium-ion battery, DILs not only have high potential window and flame retardant characteristics, but also helps to stabilize the formation of solid electrolyte interface (SEI), which can better improve the stability and reversibility of the batteries. When used in supercapacitors, DILs have a wide electrochemical window, but their large viscosity seriously hinders ion movement. Although the addition of conventional organic solvents can reduce the viscosity, the side reactions such as solvent decomposition caused by the solvation effect also seriously affect the capacitor performance. In addition, the paper also summarizes the exploration and research of DILs in zinc-air batteries, proton exchange membrane fuel cells, dye-sensitized solar cells, redox flow batteries and electrocatalysis. Finally, the problems existing in the application of DILs in electrolyte system and the main research directions in the future are summarized.

To meet the needs of sustainable energy and green development, the lithium-ion battery (LIB) market has continued to proliferate recently. However, limited by a certain life, the number of spent LIBs will also be produced. Spent LIBs will lead to resource waste and severe environmental pollution, so the recycling of spent LIBs is an inevitable key issue. Graphite is an ideal anode material and occupies a dominant position in the LIBs market due to the advantage of low cost, abundant reserves, high energy density, and long cycle life. Currently, the research on battery recycling mainly focuses on the metals in cathode material, but the recycling of anode material must be addressed. This review briefly discusses the status of LIB recycling and emphasizes the necessity of anode graphite recycling. The main failure mechanism on anode material, the effects and changes on the anode graphite material, and the characteristics of spent anode graphite were summarized. Then the research progress on the recycling of anode graphite was reviewed, including regeneration, modification, and reutilization. The recycling challenged were identified, and the prospects for the recovery and reuse technology were put forward to promote the sustainable development of the battery industry.

Energy storage is an important supporting technology for constructing a new power system with new energy as the main body, which is of great significance to achieving the goal of carbon peak and carbon neutrality. Rail gravity energy storage belongs to physical energy storage, which has the advantages of large scale, low cost, high efficiency, eco-friendly, and no self-discharge, resulting in broad application prospects. In this study, a rail gravity energy storage system model was built based on MATLAB/Simulink, and the energy loss of each component of the system in the energy storage and energy release processes were analyzed. The influence of factors such as the mass of the vehicle, the speed of the vehicle, the inclination of the slope, the height of the slope, and the rolling friction coefficient on the system efficiency and their variation rules were studied. These factors significantly reduce the speed and rolling friction coefficient, and increase the slope and height appropriately, resulting in an efficient system. Under these design conditions, the load vehicle of 160 t the speed of 20 km/h, the slope of 200 m, the slope of 7°, and the rolling friction coefficient of 0.006 was achieved. The corresponding system output power and efficiency are 1.04 MW and 76.20%, respectively.

Considering the impact of long-term uncertainty of supply and load on the robustness of the planning results of an electricity-hydrogen integrated energy storage station, a capacity planning method considering the uncertainty of multiple time scales is proposed. First, the structure of the hybrid electricity-hydrogen system is constructed, and the main operating modes of the energy storage station are designed. Second, taking into account the temporal correlation of wind, photovoltaic, electricity and hydrogen, the typical temporal scenarios of both source and load sides considering short-term uncertainty are extracted. Also, the capacity planning model of the energy storage station based on multi-scenario stochastic optimization is established to minimize the comprehensive annual cost. Then, further considering the long-term uncertainty, the planning model is improved based on the information gap decision theory. A stochastic robust hybrid planning method for energy storage stations is proposed considering long- and short-term uncertainties. Finally, the simulation is performed based on historical data of wind and photovoltaic power stations. Sensitivity analyses of critical factors, such as the energy shortage penalty cost coefficient and hydrogen price, are performed. The simulation results demonstrate that the proposed method can plan reasonably the capacity of the electric-hydrogen integrated energy storage station and improve the risk aversion ability of the hybrid electric-hydrogen system.

To improve the accuracy of the cooling system model of a Proton Exchange Membrane Fuel Cell (PEMFC) and control it conveniently and effectively, key cooling system modules, such as an expansion tank, coolant circulating pump, and radiator are constructed based on Simulink/Simscape, and the physical modeling and simulation of the fuel cell cooling system are performed. The temperature of the water-cooled fuel cell stack and the temperature difference between the coolant in and out of the stack are mainly affected by the radiator's airflow and the circulating water flow. Given the strong coupling relationship between the airflow and the circulating water flow, a combined control strategy of the coolant flow following the current control and the linear active disturbance rejection control airflow is proposed, which realizes the decoupling of the cooling fan and the circulating water pump control. Therefore, an elite genetic algorithm is proposed to optimize the parameters of Active Disturbance Rejection Control to ensure the effectiveness of the control strategy and reduce the workload of setting parameters. When the optimized control strategy is disturbed by the input, the maximum overshoot of the system becomes 1.23% and can be stabilized again within 30 s. Therefore, the temperature of the fuel cell stack can be effectively controlled. Simulation results show that the optimized control approach has excellent resilience and anti-interference ability and can efficiently regulate the stack and coolant temperature difference under the influence of step load current without interference or white noise interference.

A comprehensive energy system was developed for a large office building in north China using a photovoltaic power generator, an iron-chromium liquid flow battery, a heat pump, and water energy storage. The annual hourly energy consumption and benefit analysis of the energy system are conducted by compiling calculation programs, optimizing algorithms, and other processing methods. Economic indicators, such as the initial investment, annual energy consumption, operating cost, energy conservation rate, and life cycle cost (LCC), are used to evaluate the system's economics and design. The results indicate that the multiple energy source system has better energy conservation and economics. The optimized storage tank volume is 920 m³ with 14 heat pumps and an LCC of 13.4708 million yuan. The iron-chromium liquid flow battery stored power and heat, while the water energy storage system was used for heating and cooling storage, resulting in an annual average photovoltaic power consumption of 65.3%. At this cooling and heating load supply level, an energy storage supply of more than 67% was achieved from the total cooling and heating energy supply, of which 100% was acquired in March, September, and November.

Compressed air energy storage (CAES) can improve the reliability of power transmission to a certain extent. It is one of the most promising energy storage technologies at present, but the low-efficiency working cycle of the system limits its further development. Therefore, to improve the working cycle efficiency of the system, the working process of the CAES system is studied. For that aspect, injecting high-temperature water mist into compressed air is used to enhance the heat exchange between air and water mist, resulting in quasi-isothermal gas expansion. First, a mathematical model of quasi-isothermal expansion of compressed air is established. Second, a spray heat transfer-based quasi-isothermal expansion system of compressed air was built to conduct relevant experimental research, and the mathematical model was verified. Finally, to obtain the related performance of the compressed air quasi-isothermal expansion system, the mathematical model is used to simulate and study the changes in the air pressure and temperature in the cylinder, the parameters that affect the output work, and the energy release efficiency of the system. Compared with the adiabatic expansion, when the inlet pressure is 1 MPa, the maximum temperature difference of the air in the quasi-isothermal expansion cylinder is only 14.4% of the adiabatic expansion, the system output power increases by 147 J, and the energy release efficiency increases by 19.24%. When the spray pressure is 6 MPa and the intake pressure is 0.5 MPa, the energy release efficiency of the system can reach 81.41%. This study theoretically supports the spray heat transfer-based quasi-isothermal expansion of compressed air.

A multi-threshold adaptive clustering group equalization control method is suggested to lessen the inevitable consistency discrepancy between the cells in the energy storage battery pack. First, a single-inductor energy storage equalization topology with a simple structure, simple control, and perfect balancing function is presented and its design process of equalization principle and control signal duty cycle is examined. Second, a multi-threshold adaptive clustering cluster equalization control method is proposed. To implement the transmission of equalization energy across battery groups with various numbers of neighboring cells, the concept of cluster equalization is introduced, and a control technique for group equalization is devised based on nearby cells with minor consistency discrepancies. Finally, through the simulation experiment, it is confirmed that compared with the "single to single" equalization control method based on range or average, the proposed adaptive clustering group equalization control method enhances the equalization speed by 40.4%, 24.6%, and 17.5% respectively under the condition that the initial state of charge(SOC) distribution is high in the middle, low in both sides, high in both sides, low in the middle, and uniform distribution, while ensuring the equalization efficiency. Additionally, following equalization, each SOC's discrete degree is lower than the battery pack's average SOC. To improve the consistency difference between each cell within the storage battery pack, increase its energy utilization and cycle life, and encourage the use of energy storage battery packs, this study offers a novel equalization idea for a battery pack made up of many cells used for energy storage

Thermal runaway of lithium-ion batteries is the core issue of current electrochemical energy storage power stations regarding safety. Accurate and detailed description of the battery thermal runaway is the premise to realize the active safety warning of energy storage power stations. However, lithium-ion battery is an electrochemical system with complex nonlinear characteristics, which exhibits multi-dimensional signal characteristics during their thermal runaway evolution. It is difficult to comprehensively monitor batteries' safety and health status only by a single signal characteristic. Therefore, studying the evolution and coupling mechanism of multi-dimensional signals in the battery thermal runaway is essential. This review systematically investigated the evolution laws of characteristic signals in the four dimensions of thermal, electricity, machinery, and gas during the thermal runaway of lithium-ion batteries and analyzed the coupling characteristics between different signals. Furthermore, an active safety early warning method has prospected for energy storage batteries based on multi-dimensional sensing signals.

Battery energy storage is a powerful target for carbon neutrality. Accurate estimation of its state of energy (SOE) and state of power (SOP) is the key and foundation for the effective and reliable operation of battery energy storage. It is challenging to determine the precise values of SOE and SOP as recessive state quantities due to the intricacy of the electrochemical reaction process in batteries. Therefore, a model-based joint estimation method of SOE and SOP is suggested in this paper. Recursive least squares are utilized to create an online parameter identification technique using the Thevenin equivalent circuit model, and accurate model parameters are achieved. To address the prediction problem under constant power demand, a multi-step power prediction method is proposed to enhance the prediction accuracy of SOP. An additional joint estimation approach of SOE and SOP is suggested in conjunction with the expanded Kalman filter algorithm. The feasibility of the algorithm is verified by experiments. The findings demonstrate that, even in the presence of significant starting errors, the suggested method's maximum voltage and SOE prediction errors are both less than 2%, resulting in precise SOP prediction.

With the vigorous development of the energy storage industry, the application of electrochemical energy storage continues to expand, and the most typical core is the lithium-ion battery. However, recently, fire and explosion accidents have occurred frequently in electrochemical energy storage power stations, which is a widespread concern in society. The safety of lithium-ion batteries affects the safety of energy storage power stations. Analyzing the thermal runaway behavior and explosion characteristics of lithium-ion batteries for energy storage is the key to effectively prevent and control fire accidents in energy storage power stations. The research object of this study is the commonly used 280 Ah lithium iron phosphate battery in the energy storage industry. Based on the lithium-ion battery thermal runaway and gas production analysis test platforms, the thermal runaway of the battery was triggered by heating, and its heat production, mass loss, and gas production were analyzed. Fourier-transform infrared spectroscopy (FTIR), and a hydrogen sensor were further used to measure the gas production component during the thermal runaway. The proportion of H₂ and CO obtained by convolution analysis accounted for 36.8% and 44.2%, respectively. The 1∶1 model of the battery energy storage liquid-cooled tank was established by FLACS software, and the dynamic pressure and flame hazard of gas production from lithium iron phosphate batteries under different conditions were analyzed. The study found that the explosion behavior in the battery energy storage compartment was affected by the position of the pressure relief plate inside the compartment, the opening pressure, and the surrounding obstacles. When the opening pressure of the cabin door increases from 10 to 100 kPa, the peak explosion overpressure increases by 2.15 times. This research can provide a reference for the early warning of lithium-ion battery fire accidents, container structure, and explosion-proof design of energy storage power stations.

It is essential to estimate a battery's state of health. This paper constructs a back propagation (BP) neural network optimized based on the improved firefly algorithm (FA) to estimate the state of health of lithium-ion batteries. The aim is to address the shortcomings of traditional modeling methods, such as poor estimation accuracy, numerous parameters, complex calculation, and longtime consumption. The weights and thresholds of the BP neural network are optimized using the FA's global optimization ability and fast convergence speed. Levy flight is introduced to improve the global search ability, expand the search range, and improve the estimation accuracy. The lithium-ion battery dataset of NASA Ames Research Center is used to train and estimate the algorithms before and after improvement and optimization and compare the advantages and disadvantages of each algorithm. Results show that compared with the BP neural network algorithm and FA for optimizing the BP neural network (FA-BP) algorithm, Levy flight improved firefly algorithm to optimize the BP neural network (LFFA-BP) algorithm has a higher determination coefficient, smaller error fluctuation range, higher estimation accuracy, and specific practical value.

Energy storage batteries are widely used, and accurate estimation of the state of charge (SOC) of these batteries is of great significance in improving the state of battery health. In scenarios like energy storage power stations, lead-carbon batteries have drawn increasing interest as a novel-type energy storage battery with high performance, low cost, and high safety. However, there is still no lead-carbon battery SOC calculation available. Following the galvanostatic intermittent titration technique, this study first explores the relationship between the SOC and open circuit voltage of lead-carbon batteries. Then, voltammetry characteristic data of lead-carbon batteries are obtained through hybrid pulse power characteristic test, the equivalent circuit models of first-order Thevenin and first-order PNGV are established, and the parameters of the two equivalent circuit models are identified using a random algorithm based on the surrogate model and sensitivity analysis. On this basis, the extended Kalman filter (EKF) algorithm is used to estimate the SOC of lead-carbon batteries, and noise interference is considered during the estimation process. When the initial value of the lead-carbon battery SOC is unknown, the EKF algorithm cannot accurately estimate its SOC. Therefore, to address the drawbacks of EKF, this study proposes an adaptive extended Kalman filter to estimate the state of lead-carbon batteries. Results show that in the presence of noise and an unknown initial SOC value, the adaptive extended Kalman filter algorithm can estimate the SOC of lead-carbon batteries more accurately than the EKF algorithm and ampere-hour integration method, and the error is the smallest (3.91%) when the initial SOC value is 0.9, which verifies the effectiveness and applicability of the algorithm and improves the accuracy and reliability of SOC estimation of lead-carbon batteries.

This study established a classic P2D electrochemical simulation model for lithium-ion batteries. The effects of five parameters on the discharge capacity of the battery were quantitatively analyzed by simulation method, including the diameter of active particles on the cathode and anode, the thickness of the cathode and anode, and the separator thickness, which are of great significance to provide guidelines for optimizations. The simulation results showed that the diameter of active particles on the cathode could influence the tendency of capacity vs. voltage curves after the voltage is higher than 3.3 V. In contrast, the diameter of negative active particles affects the entire voltage window of the capacity vs. voltage curves. Secondly, the thickness of cathode electrode impacts the entire voltage of capacity vs. voltage curves. The thickness of the anode electrode on capacity vs. voltage curves leads to a fluctuation below the voltage of 3.6 V. According to the simulation results, only the thicknesses of cathode and anode electrodes give positive response to the battery discharge capacity. At the same time, the diameter of negative particles negatively responds to the battery discharge capacity. However, cathode particle diameter and separator thickness are insensitive to discharge capacity. Moreover, all the parameters accord with the quadratic equations.

As a passive safety measure to prevent the thermal runaway of the battery system, the vent plays a very essential role in cell design. After the cell has reached thermal runaway, the pressure relief procedure is significantly impacted by the opening pressure, area, and position of the vent. This paper mainly presents the pressure relief process of the vent opening caused by heat and gas production after the cell thermal runaway. Through theoretical calculation, experimental test and simulation analysis, the pressure relief features of the vent are systematically described and analyzed. First, the pressure relief process of the vent is examined theoretically based on the basic principles and equations of fluid mechanics, and the basic state of the pressure relief choke flow after the vent is opened in the process of thermal runaway is expounded; Second, by performing two kinds of experiments of heating thermal runaway and overcharging thermal runaway of the cell, the temperature of the jerry roll and the internal pressure of the cell were monitored in real time, to determine the heat and gas production rate before the vent was opened; Finally, a simulation of the cell's pressure relief, gas production, and heat output are performed. The system model for the vent's pressure relief is built using COMSOL, and impacting elements including the vent's opening pressure, area, and position are categorized and simulated. Additionally, the simulation results and test data from experiments are compared. A more optimized structure design of the vent is obtained, which provides a certain reference for the optimal design of the power battery.

With the increasing proportion of wind power and photovoltaic power grids, the problem of wind and solar abandonment caused by an insufficient peak shaving capacity of cogeneration units becomes more evident during the hot weather. Phase change energy storage technology positively improves the flexibility and robustness of the integrated energy system. Therefore, this study establishes a comprehensive energy system model of wind/solar/gas cogeneration based on the phase change energy storage system (PCESS) with a heat pump. In this model, the least amount of wind and solar abandonment and the lowest total operating cost are optimization objectives, while the thermoelectric power balance, the output of each system's energy module, and the capacity status of energy storage equipment are constraints. Then, a dual fitness particleswarm optimization algorithm based on elite reverse learning is proposed. The elite reverse learning strategy enhances the algorithm's performance in finding solutions. The dual fitness algorithm solves the problem that the penalty function factor is difficult to obtain. Through case calculation, the improved optimization algorithm has a stronger global optimization ability and a faster calculation speed. According to the calculations, adding PCESS can effectively improve the system's wind power and photovoltaic energy utilization efficiency. The system's wind/solar output decreases from 722.1 kWh/d without PCESS to 163.4 kWh/d (a 77.4% decrease). PCESS improves the operation stability of cogeneration units in the system and reduces natural gas consumption. The system's operating cost decreases from 2488.5 to 2389.5 CNY/d, bringing remarkable economic benefits.

To explore the method of reducing automobile carbon emissions, it is vital to understand the carbon emission law of automobiles over their whole life cycle. To obtain the carbon emission law of electric vehicles in the whole life cycle, a carbon emission calculation model from material acquisition to vehicle production, use, recycling, and reuse is established by using the carbon emission factor method. The carbon emission of a BYD E6 car, for instance, is calculated using data on power structures from 2021, and the characteristics of carbon emissions are examined from the perspectives of various life cycle stages, vehicle components, and materials, as well as the potential for carbon emission reduction offered by power battery recycling technology and power structure. The results demonstrate that: the proportion of carbon emissions in the use stage is the highest, reaching 88.4%, followed by the material acquisition stage, accounting for 7.8%, and the carbon emissions in the recycling and reuse stage are negative, leading to positive benefits; Recovery and reuse can effectively reduce carbon emissions, accounting for 22.1% of the total carbon emissions, The power battery adopting echelon utilization technology shows the highest reuse rate, which reduces the carbon emission proportion of the power battery to 7.3% at the material acquisition stage; When the proportion of clean energy in the power structure reaches 67.5%, the carbon emissions of the single vehicle will be 54.6% of the emissions in 2021; When the proportion of clean energy in the power structure reaches 96%, the carbon emissions of the single vehicle will be 20.3% of the emissions in 2021. The research findings give China's policy on reducing carbon emissions from cars and industry technology a scientific foundation.

New energy is green and environment-friendly renewable energy that can reduce environmental pollution and alleviate energy crisis. It is considered one of the most decisive technology fields in the future of world economic development. Transformation, storage, and utilization of the new energy depend on developing new energy materials, devices, and energy storage science. Under the background of the national energy plan and double carbon strategy, requirements for talents training of majors in China's colleges and universities in new energy materials and devices are constantly updated with the development of social economy and new energy industry. The major, new energy materials and devices, was approved in 2019 at the Nanjing University of Aeronautics and Astronautics and has been under development ever since. Presently, there are 124 undergraduates. This paper will discuss three aspects: setting characteristic training objectives, constructing an interdisciplinary curriculum system, and training of systematic practical ability. The training objectives of the major are analyzed in detail, including the characteristics of high-level comprehensive technical talents training, traditional advantages of aerospace, and a close combination between new energy industry demands and technological development. Herein, the systematic curriculum system with the following characteristics: solid foundation, integration, intersection, diverse directions, and emphasis on practice, is presented. A complete practical ability training system is formed through the coordination of the internal and external bases, which are jointly constructed following basic, innovative, and comprehensive practices. Exploration of a new talent training model that meets the need of society's economy and new energy industry development was attempted to provide useful suggestions and references for further developing new energy materials and devices major in the future.

The Natural Language Process (NLP) models such as ChatGPT and GPT-3 have been discussed recently in academia and the Nature Publishing Group allows the authors to use ChatGPT to assist academic research. This means machine learning especially NLP has been integrated into the academia and will change the research paradigm. It exists opportunity and challenge for the battery researchers especially in replacing monotonous repetitive work. What can the researchers do for batteries, how to construct and use it to assist battery researching and the problem existing in it have not been discussed in details. Based on it, we write this perspective to explain above questions especially the following: ① The problems existing in NLP models; ② What can the battery practitioners do to meet these opportunities and challenges; and ③ How to learn the basic knowledge and construct battery model. All discussions are based on our recent works and the use of models and we hope it will offer initial guidance for battery researchers.