Layered Li-Mn-rich materials (LMR) are promising to be next generation cathodes for lithium-ion batteries due to their high specific capacity (>250 mAh/g) and low cost. It has been nearly 30 years since the discovery of LMR material, but it has never been commercialized for the following reasons: During the cycling process, Mn³⁺ migrates into Li sites makes the layered structure transform to spinel structure, resulting in a serious discharge voltage decay, which causing serious energy loss and bringing great challenges to battery management. The low electronic conductivity of Li₂MnO₃ makes LMR material have poor rate capability and lower electrode density results in lower volume energy density of LMR. In addition, the LMR materials need to be at high voltage (>4.55 V) to show high capacity, but the electrolyte at high voltage is easy to oxidize and decompose, accompanied by the release of lattice oxygen into O₂, the above problems seriously affected LMR commercialization process. Based on the research and development results of LMR materials over the years, this paper reviews the research progress of LMR materials in the understanding of charge and discharge mechanism, precursor process route selection, modification effect and mechanism of bulk doping, surface coating, liquid and gas phase post-treatment, and the design of new special structures such as O2/O3 composite structure and single crystal structure. In addition, the future development direction and commercial prospect of LMR materials are prospected to help the industrial development of LMR materials.

Na-ion batteries (NIBs) are considered the most promising new-generation energy storage systems to replace Li-ion batteries (LIBs) because of their abundant resources and environmental friendliness. However, the radius of sodium ions is larger than that of lithium ions, and traditional Li-ion battery anode materials have difficulties in the insertion/extraction of sodium ions during the charging and discharging process, which easily leads to the collapse of the material structure. Currently, the lack of suitable anode materials is still one of the main obstacles limiting the large-scale application of NIBs. Compared with traditional NIBs anode materials (carbon materials, metal oxides, metal phosphides, etc.), layered metal dichalcogenides (TMDs) have been extensively studied due to their unique layered structures that "extra" store Na ions and effectively mitigate volume changes in electrochemical reactions. In this paper, three common synthesis methods for TMDs materials will firstly be introduced, namely water/solvothermal, chemical vapor deposition, liquid phase exfoliation method. Then, the research progress of several commonly used TMDs (MoS2, SnS2, WS2, VS2) as NIBs anodes is reviewed. Finally, the advantages and disadvantages of different TMDs material synthesis methods will be compared, and the current challenges and future development prospects will be further prospected, so as to provide some theoretical and scientific references for further promoting the industrial application of TMDs in NIBs.

The tremendous development of the electric vehicle (EV) industry is of great significance for China to achieve the goal of carbon peak and carbon neutrality. As the power source and core component of the EVs, the power batteries will inevitably enter the end-of-life stage, and the efficient and cleaner recycling and disposal of spent power batteries is vital for the sustainable development of the industry. The anode materials are one of the most important factors determining the performance of the power batteries. Currently, graphite has become the mainstream commercial anode material due to its properties such as higher conductivity, higher reversible capacity, and stable cycling performance compared with the high-value critical metals such as lithium, nickel, and cobalt. There are very few industrial recycling solutions that are effective and clean for anode graphite materials. The main application fields of graphite resources globally and specifically in China are based on the systematic analysis of reserved outputs, and the advances in the recent development of technologies for the recycling and disposal of anode graphite from spent lithium-ion batteries. The application fields for the recovered graphite and the corresponding products are summarized, whereas emphasis is laid on the physical and chemical recycling technologies for anode graphite. Finally, it is proposed that the research and development of effective and cleaner industrial recycling and disposal systems for anode graphite should be strengthened. Also the utilization approaches for the recovered graphite, and the corresponding products should be expanded.

Lithium bistrifluoromethanesulfonimide (LiTFSI) was used as a lithium salt. Glass fiber cloth, polyethylene oxide (PEO), 1-ethyl-3-methylimidazole bis-trifluoromethanesulfonimide salt ([EMIM]TFSI) and LLZO nanoparticles were used as raw materials. Glass fiber-based multilayer composite solid electrolyte membranes with different LLZO contents were prepared by the solution casting method. Enlarging the amorphous phase region of PEO and improving the interface compatibility of the film can improve the ionic conductivity of the film, and at the same time, using Si-O and -OH functional groups on the surface of glass fiber cloth can guide the uniform deposition of lithium ions and inhibit the growth of lithium dendrites. The results show that under the condition of 30 ℃, the ionic conductivity of glass fiber cloth/PEO/ILs/LLZO (SPE) composite solid electrolyte membrane with a weight ratio of 5% LLZO is 3.53 × 10^-4S/cm, and the working voltage window is 5.18 V. The Li⁺ migration number is 0.33. The prepared LFP/SPE/Li and NCM₆₂₂/SPE/Li solid state batteries have a discharge capacity of 165 mAh/g and 226 mAh/g at 0.1 C, respectively. Among them, the LFP/SPE/LI battery circulates 120 cycles at 0.5 C, a discharge capacity of 120 mAh/g, and a capacity retention rate of 99.8%. In addition, the impedance change is small before and after cycling, and it has excellent interfacial stability.

The compatibility between battery materials affects their performance. The performance of batteries can be improved by adding 12-crown-4, 15-crown-5, 18-crown-6, and other aliphatic-crown ethers to the electrolyte, which improves the compatibility. This article introduced the molecular structure of crown ethers, which determines their surface-interface activities and coordination inclusion capabilities. In addition, it reviews the application history of aliphatic crown ethers in lithium-ion battery electrolytes, summarizes the effects of crown ether on the inhibition of the irregular precipitation of metals, forming films on the electrode surface, reducing solvent side reactions, solubilizing electrolytes, improving ionic conductivity, improving the performance of solid electrolytes, etc. The application of aliphatic crown ethers in electrolytes is limited by the high production costs of the Williamson ether-synthesis process, which has low selectivity, many by-products, and difficult purification. Oligomerization using ethylene oxide is a preferable process for producing aliphatic crown ethers; however, it needs to be improved to avoid the use of fluorine-containing salts. Finally, there are prospects for the application of aliphatic-crown ethers in electrolytes.

The nonsolvent induced phase separation (NIPS) method was used to create Poly(m-phenylene isophthalamide)/solid-state ionic conductor composite membranes (PMIA-LATP-PEO) with high thermal stability and excellent electrolyte wettability. Poly(m-phenylene isophthalamide)(PMIA) serves as an insulation and high-temperature stability matrix in the composite system. Li_1.3Al_0.3Ti_1.7(PO₄)₃(LATP) with a sodium super ion conductor (NASICON) structure is a solid-state ionic conductor evenly distributed in the membrane for the enhancement of the ionic conductivity of the composite membrane. Poly (ethylene oxide) (PEO) plays a role in adjusting the pore size in the process of membrane preparation and can improve the interface stability between membranes with lithium metal. The morphology and element distribution of membranes were studied using scanning electron microscopy (SEM) and energy spectrum analysis (EDS). Differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and thermal shrinkage methods were used to characterize the thermal stability of the membranes. The electrochemical properties of the membranes, such as ionic conductivity and lithium-ion transference number, were measured using electrochemical technology. The cycling performance and rate performance of the composite membranes were measured in the LiFePO₄||Li cells. PMIA-LATP-PEO membrane has a dense pore structure and reliable insulation and maintains a stable dimensional shape at 200 ℃. The lithium ionic conductivity is 2.07×10^-3 S/cm^{(25 ℃) for electrochemical performance, and the transference number of lithium-ion is 0.75. Furthermore, the PMIA-PEO-LATP membrane is resistant to lithium metal. In Li||Li symmetrical cells, the PMIA-PEO-LATP membrane can run stably for over 1000 h at 0.5 mA/cm2. Furthermore, the PMIA-PEO-LATP membrane can inhibit the growth of lithium dendrites, allowing LiFePO₄||Li cells to show superior cycling stability.}

To prevent the leakage of materials during the phase-change process, low-temperature phase-change microcapsules with pentadecane (Pen) as the core material and urea-formaldehyde resin (UF) as the wall material were prepared using insitu polymerization. The effect of heating rate, polymerization pH, and polymerization speed on the microcapsules preparation was studied. The morphology, chemical composition, thermodynamic properties, and the particle-size distribution of microcapsules were tested using SEM, FT-IR, DSC, and Malvern laser particle-size analyzer. A heating rate of 1.0 ℃/min, polymerization pH value of 3.5, and polymerization speed of 500 r/min are the optimal preparation conditions for pentadecane microcapsules. The microcapsules prepared under the above conditions have spherical morphology, smooth surface, a few UF particle adherence, and the particle-size distribution is uniform. The phase-change temperature and latent heat of the microcapsules are 8.20 ℃ and 115.3 J/g, respectively. The average particle size of the microcapsules is 50.0 μm, and the encapsulation rate reaches 77.3%. The experimental results show that the core and wall materials are held by physical forces. The microcapsules have good heat storage performance and thermal stability. Pentadecane microcapsules are dispersed with different mass fractions of ethanol solution as the base solution. A stable latent-heat functional fluid (LHFF) is obtained using a static experiment for 24 h. The LHFF is the most stable in the base solution with 70 wt% ethanol. The thermal conductivity and viscosity of the LHFF are tested and analyzed using a thermal conductivity tester and rotational viscometer. The thermal conductivity of the LHFF increases with an increase in temperature and decreases with an increase in the mass fraction of microcapsules. The viscosity of the LHFF decreases with an increase in temperature and increases with an increase in the mass fraction of microcapsules. As the secondary refrigerant of the air conditioning system, LHFF can improve the performance of the refrigeration unit, reduce the energy consumption of the pump, and improve the economy of cold storage of the air conditioning system.

A form-stabled phase change composite SEPS/OP10E C-PCMs with deformable, strong mechanical properties and casting and molding properties was prepared via the melting blending method using the thermoplastic elastomer SEPS and OP10E through the physical cross-linking mechanism. Herein, PEG 2000 was added to enhance the mechanical properties and the mechanism of physical cross-linking and mechanical property enhancement was proved. Simultaneously, in this work, thermal storage, thermal stability, and mechanical properties were investigated by various test and characterization methods, including differential scanning calorimetry (DSC), thermal analysis (TG), tension-stress test, etc., to explore its heat storage performance, thermal stability, and mechanical properties. The experimental results show that SEPS/OP10E-PEG 2000 exhibits a high latent heat value and no paraffin leakage even after 50 heating-cooling cycles, which proves its good thermal stability, and the maximum tensile rate of 652.3%, showing strong mechanical properties. Additionally, SEPS/OP10E-PEG 2000 was applied to a cold storage tank, which can be maintained at 7-9 ℃ for 2.6 h. This novel composite phase change material with special pouring performance and good thermal characteristics reduces the space proportion of thermal storage materials in cold chain transportation, thus enhancing the precision temperature control ability and cold storage performance, effectively saving the storage space of cold chain transportation simultaneously.

The vacuum absorption and film vacuum encapsulation was utilized using the abundant pore structure of expanded vermiculite, a type of sodium sulfate decahydrate/EV film phase change composite (film phase change material). The supercooling and phase separation of film composites were analyzed by scanning electron microscopy, X-ray diffraction, and self-made temperature reference phase transition latent heat test chamber. The result shows that when 50% EV is added to sodium sulfate decahydrate, the pore loading capacity of EV reaches saturation. Also under the combined cation of EV and borax, the supercooling degree of the film phase change composite measured by step cooling curve was 0.5 ℃. However, after the film vacuum encapsulation, the sodium sulfate decahydrate is uniformly loaded inside the EV-layered structure. The latent heat of the film phase change composite with 50% EV content is more than 105 J/g, and it should be stable after three hundred phase change cycles. Also, after five hundred phase change cycles, the latent heat remains above 90 J/g, and the latent heat retention rate is 83.45%. The cyclic performance is better than atmospheric pressure encapsulating, and the film vacuum encapsulation can obtain a better loading effect of expanded vermiculite on sodium sulfate decahydrate. The film phase change composite can effectively inhibit the supercooling, and phase separation of sodium sulfate decahydrate, which has a high phase change cycle life.

Amorphous and nanocrystalline PrMg₁₂+x%Ni (x=0, 10, 20, or 30) alloys were prepared by mechanical milling, and the effects of the nickel content on the thermodynamics and kinetics of hydrogen storage in the alloys were studied systematically. The phase composition and microstructure of the alloy were analyzed by X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM). The PrMg₁₂+x%Ni (x=0, 10, 20, or 30) alloy was mainly amorphous and nanocrystalline. Before adding nickel, the main phases before and after hydrogen absorption were the PrMg₁₂ phase, MgH₂ phase, and PrH_2.92 phase, respectively. After adding nickel, the main phases before and after hydrogen absorption were a Ni phase, PrMg₁₂ phase, MgH₂ phase, and Mg₂NiH₄ phase. The P-C-T curves and hydrogen absorption and desorption kinetic curves of the alloy were measured using a Sieverts apparatus, and the thermodynamic and kinetic parameters were calculated by combining the Van't Hoff equation, the JMAK model, and the Arrhenius method. The hydrogen desorption enthalpy of the alloy hydride decreased from 89.881 kJ/mol to 82.764 kJ/mol as the Ni content was increased from 0% to 30%, and the hydrogen desorption activation energy decreased from 126 kJ/mol to 90 kJ/mol. Hence, adding nickel can significantly improve the hydrogen release thermodynamics and kinetics of ball-milled PrMg₁₂-type alloy hydrides.

A phase change material (PCM) melting test apparatus was constructed, metal fins were added to the PCM, and paraffin was used as the PCM. Subsequently, high thermal conductivity nanoparticles and metal fins were added to the PCM. The temperature data acquisition system was used to record the internal temperature change trend in the melting process of PCM in order to analyze the influence of the mass fraction of nanoparticles and the number of fins on the heat transfer performance of PCM. Also, the results show that the addition of nanoparticles can effectively improve the temperature of PCM. The temperature rise rate of 0.06% graphene/PCM is higher than the heat transfer effect, and it is better than other components of graphene/PCM. Moreover, the addition of fins can improve the internal temperature response of PCM, and the overall heat transfer performance of 9 fins/PCM is better than that of other fins/PCM. The combination of nanoparticles and finned structure can improve the heat transfer performance of PCM. In the first 60 min of the experiment, the temperature rise of 9 fins and 0.06% graphene/PCM was faster than that of other enhanced combinations. From 60 to 90 min, the heat transfer performance of 9 fins and 0.09% graphene/PCM was enhanced, with the highest temperature rise. Therefore, they are excellent combinations in the experiment to enhance PCM heat transfer performance.

Adding porous media is an effective way to improve the thermal conductivity of PCM and reduce its melting time. By establishing a physical model of inorganic hydrated salt composite phase change material (CPCM) with irregularly distributed porous skeleton, the influences of porosity, pore size, and skeleton shape on thermal storage characteristics were studied numerically. The results demonstrated that the melting rate of CPCM increased with smaller porosity. Under gravity driving force caused by the density difference between solid and liquid CPCM, the natural convection phenomenon was found to promote the melting process. At a porosity of 0.80, the porous skeleton with smaller pore size had a larger surface area, which results in absorption of more heat flux and reduced melting time. CPCM possessing tetrahedral skeletons with a maximum specific surface of 30.02 mm^-1 completed melting in 41 s, which is 13.5 s faster than an icosahedron with a specific surface of 19.93 mm^-1. Although the smaller porosity was beneficial to melting, the heat storage capacity was reduced. According to the numerical results, the determined equilibrium porosity was 0.80, which may help balance the acceleration of the melting rate and heat storage capacity, as well as make the effective thermal conductivity reach 8.07 W/(m·K). Thus, this paper provides a theoretical basis and reference for low-temperature heat storage materials.

When designing a power battery-pack cooling system, the use of finite element modeling to estimate the battery temperature cannot be simulated in real-time using the control algorithm. Thus, an electrothermal-coupling model built in MATLAB/Simulink based on the heat generation and dissipation characteristics of the battery is proposed to estimate the temperature change of the battery pack in real-time. The electrothermal-coupling model of the power battery is composed of two parts: the battery equivalent circuit and thermal models. The battery charge and discharge test is used, and the genetic algorithm is used to identify the equivalent circuit model parameters under the time-varying conditions offline. The thermal model parameters are theoretically analyzed. Heat generation and dissipation methods were calculated. The equivalent circuit and battery thermal models are coupled with each other using the relationship between internal resistance and temperature, thus, establishing a single battery electrothermal-coupled model. The temperature model of the cooling channel is established to improve the electrothermal-coupling model of the battery pack by analyzing the heat-transfer mode of the battery module. The temperature difference between the battery-coupling model and numerical simulation using STAR-CCM+ is 1 ℃; the terminal-voltage simulation results of the electrothermal-coupling model can track the measured terminal voltage and can describe the battery pack at the same time. The Temperature distribution during the internal cooling process. The research results show that the electrothermal-coupled model can estimate the temperature change of the actual battery pack to shorten the development cycle of the thermal management control strategy for the battery pack.

Recently, electric vehicles have developed due to their energy-saving, environmental protection, and high energy-conversion efficiency. At low temperatures, the performance of lithium-ion batteries, such as discharge power and capacity, is attenuated. This has affected the development and popularization of electric vehicles in the cold areas of north China. Therefore, it is important to understand how lithium-ion batteries reliably, efficiently, and safely heat at low temperatures. The electrical and thermal characteristics of the battery are obtained using the ternary lithium prismatic battery as the research objectives by testing the low-temperature characteristics of the battery under different working conditions. The cell electrothermal-coupling model is established, and a low-temperature heating-simulation model of the battery is obtained by fitting experimental data with the neural network method. The accuracy of the simulation model is verified using the temperature-rise experiments for the battery under different working conditions. A multistage constant-current composite-heating method is proposed, and a multiobjective nonlinear optimization model of battery aging, heating time, and capacity gain is established. The relationship between battery aging, heating time, and capacity gain is revealed, and the evaluation weighting matrix is obtained. The balanced heating strategy of the cell is obtained using the nondominated sorting genetic algorithm-?Ⅱ(NSGA-?Ⅱ) and technique for order preference by similarity to ideal solution (TOPSIS), and the effect of different initial states of the battery on the optimization objective is explored. According to the different initial states of the battery, the heating-current database of the cell is established based on the balanced heating strategy. When the initial temperature of the battery is -20 ℃, the heating time to 10 ℃ is 253 s, the capacity gain is 4.72 Ah, the battery aging is 0.482?, and the peak power gain is 1104 W.

The efficiency, life, and safety of lithium batteries are influenced by the lithium battery management system. The control, thermal management, and fault diagnosis of the battery management system depend on the accuracy of the battery's thermal process model. However, the thermal process of the lithium battery is a distributed parameter system with strong nonlinear characteristics. The temperature distribution inside the battery is spatiotemporally coupled and has infinite dimension characteristics, making modeling extremely challenging. To solve these problems, a Laplacian eigenmaps-extreme learning machine (LE-ELM)-based spatiotemporal modeling method for the thermal process of lithium batteries is proposed. First, a local nonlinear dimension reduction method based on LE is developed to learn the spatial basis function to represent the inherent nonlinear topological feature of the original system. Second, a low-dimensional representation of the original data can be generated using time/space separation and the spatial basis functions. Then, ELM is used to approximate the low-order time-series model with the low-dimensional representation and the corresponding current and voltage input signals. Finally, the spatiotemporal temperature distribution can be reconstructed using time/space synthesis. A thermal process of ternary soft-pack lithium battery was modeled using our proposed algorithm to verify the proposed method.

All-vanadium redox flow batteries are widely used in the field of large-scale energy storage because of their freedom of location, high efficiency, long life, and high safety. The existing battery, on the other hand, has a single structure and cannot meet the needs of the rapidly developing energy storage field. A numerical simulation method is used to establish a mathematical and physical model for the coupling of electrochemical reactions and heat and mass transfer inside the battery cell to achieve the new radial flow all-vanadium flow battery cells. The distribution law of multi-physics coupling transport characteristics is obtained for different inlet quantities. Ion concentration field, electrolyte velocity field, voltage drop, and electric potential distribution law are all included. The results show that optimizing the number of electrolyte inlets can effectively improve electrolyte transport performance in porous electrodes, improve the uniformity of the ion concentration distribution in porous electrodes, weaken ion concentration polarization, increase the electrode potential, and enhance the battery performance. Simultaneously, the electrolyte distribution channel is set at the electrolyte flow inlet, thereby effectively reducing electrolyte flow resistance, improving electrolyte distribution uniformity, and improving battery performance. The simulation research results can be used to optimize the design of a flow battery.

The participation of energy storage batteries in the primary frequency regulation of the power grid has been studied extensively to improve the frequency regulation characteristics of the power grid by energy storage batteries. First, the frequency characteristic model of a high permeability new energy regional power grid with an energy storage battery was established, and its amplitude-frequency characteristics were analyzed. The addition of energy storage can effectively improve the frequency stability of the power grid. A model-free self-adaptive energy storage control strategy considering the battery state of charge and based on the input and output data of the energy storage system is proposed to ensure the state of charge (SOC) holding effect of the energy storage battery, the frequency modulation demand of the power grid, and the uncertainty of the accurate mathematical model of the energy storage battery. The corresponding frequency modulation effect and charge state holding effect indices were given. Finally, a typical high permeability new energy regional power grid frequency modulation model was simulated in Matlab/Simulink. The results showed that the proposed strategy could improve the anti-interference and self-adaptive ability of the power grid. Compared to traditional control strategies, the proposed strategy had a significant frequency modulation effect under step load disturbance. In the case of a longterm load disturbance (continuous), the state of the charge index of the proposed strategy was the best, and the frequency modulation effect index was significant. The simulation results verified the feasibility and advantages of the proposed strategy. This paper adopts the data-driven research method instead of the traditional model method, which removes the strong dependence on the mathematical model of the controlled system, helps promote the energy storage battery to participate in the more efficient application of power grid frequency regulation, and provides more ideas for accelerating the dual carbon goal.

The power battery of the new energy tram operates intermittently and generates significant heat during charging and discharging, with hysteresis in heat transfer from the inside of the battery module to the surface. Generally, various forms of heat dissipation devices need to be configured. When the thermal management system of the battery is designed using an inverter air conditioner, the battery can control the temperature within a reasonable range using its heat pump characteristics. This paper introduces a multi temperature fusion temperature zone control method suitable for this thermal management system, which primarily consists of a compressor frequency calculation method and dynamic temperature interval control. Based on the return air temperature, the ambient temperature is introduced to correct it as well as improve the air conditioner's operation efficiency; the battery temperature is introduced to make a secondary correction as well as improve the response speed of the air conditioner, and the corrected temperature is used to participate in the frequency calculation of the compressor. The temperature in the box is controlled as a wide range of temperature range, which is dynamically adjusted according to the change trend of return air temperature, so that the cooling or heating time of air conditioner is reduced and the abnormal rise of return air temperature is suppressed. The frequency conversion speed regulation control methods of the internal fan and condensing fan are also introduced. A comparative experimental test was performed on the battery box (and air conditioner) using this method. The energy consumption of the air conditioner is reduced by about 4% and the maximum temperature of the battery is reduced by nearly 2 ℃ compared with the comparative control method. The results show that the method can not only realize the demand for temperature regulation of the battery box and optimizes the battery environment, but also reduce the energy consumption of the air conditioner. The power battery box with the thermal management system has been installed and is in use on the tram.

One of the development directions to meet the "sustainable development" policy and achieve "carbon neutrality" is new energy vehicles. With the increasing popularity of electric vehicles, the safety of onboard lithium-ion power batteries has received increased attention. Thermal, electrical, and mechanical abuse will result in battery combustion and explosion. As a result, research into thermal runaway suppression of power batteries is important in practice. In this study, a 202 Ah lithium iron phosphate battery box experimental platform for electric buses is built. The inhibitory effects of heptafluoropropane on the thermal runaway of lithium-ion batteries; the inhibitory effects of heptafluoropropane on the thermal runaway of lithium-ion battery backpacks; and the protective effects of heptafluoropropane on the thermal runaway of lithium-ion battery boxes are analyzed using three aspects: fire extinguishing agent dose; spraying time; and spraying mode. The results show that the hose with bilateral gap holes can spray 1.8 kg of fire extinguishing agent heptafluoropropane (at a rate of 0.06 kg/s) and effectively inhibit thermal runaway. It has also been found that the critical temperature for lithium iron phosphate battery protection is 85 ℃. A fire extinguishing system for electric buses with a trigger temperature of 80 ℃ is designed within the guaranteed margin. The results show that battery performance does not change significantly before and after fire extinguishing, and that the fire extinguishing system can provide safety guarantees. This study provides an experimental foundation for the research and development of vehicle heptafluoropropane fire extinguishing systems and helps in promoting the application of lithium-ion battery-electric bus fire extinguishing devices.

Energy storage (ES) is a key technology that promotes the transition of energy consumption from fossil fuels to renewable energy. ES plays an important role in improving the consumption rate of clean energy, ensuring a stable operation of the power system, improving the thermal power plant's efficiency, and enhancing its power quality. This study focuses on the ES system configuration for the primary frequency regulation of the renewable power plants. This paper thoroughly considers the output characteristics and costs of different ES technologies, life cycle of the ES system, related economic issues, and several other factors to develop a hybrid ES configuration strategy for the renewable power plants. Based on multi-constrained targets, including power and energy balance, state-of-charge limits, statistics of the ES output confidence level, etc., the numerical analysis theories, including the multi-time-scale wavelet analysis, ES capacity iterative optimization algorithm, and rain-flow counting battery life prediction model are used to develop the ES system configuration methods. Based on MATLAB, a dedicated calculation tool is developed. This paper verifies the developed hybrid ES configuration methods through a 400 MW wind farm participating in the primary frequency regulation.

As an important means of improving new energy consumption, under the background of "carbon peaking and carbon neutrality," which requires vigorous development of new energy sources such as wind and solar, the "new energy + energy storage" model becomes the mainstream trend of new energy development during the country's "14th Five-Year Plan" period. Existing review articles on energy storage primarily summarize the development of various energy storage ontology technologies and the application scenarios in the power system. There is few research on energy storage optimization, especially on the new energy side energy storage, so research storage capacity in the new optimized configuration technology on the energy side is necessary. The development status of the new energy side is included in the development of the new energy side, such as policies issued by the province of "14th Five-Year Plan," domestic typical demonstration projects and application scenarios. Secondly, two key issues in energy storage optimization configuration technology are discussed, which are system selection and system planning. In system selection, the advantages and disadvantages and applicable scenarios of various battery types are compared and analyzed; in terms of building the storage planning model, consideration of different factors such as uncertainty, economic, environmental protection, and technical nature on planning models, listing specific mathematical expressions and corresponding planning methods. Finally, key content for the development of energy storage, system selection, optimization model, and optimization of the development of the simulation software platform for the development of the new energy side, the development of the design, and optimization of the simulation software platform, to make a constructive advice for future new energy sides. Configure the construction of the energy storage actual project to provide reference and reference.

The features of distributed energy storage are decentralization and flexibility, and the coordination of multiple distributed energy storage can address the problem of single energy storage's poor adjustment ability and limited range, as well as boost the capacity of new energy consumption and increase the pace of new energy use. This research establishes a photovoltaic power station, two distributed energy storage system models, examines the output of the photovoltaic power station, and uses the features of the energy storage system to track the photovoltaic output to develop an objective function with the minimum output of the dispersed energy storage system as the goal, combined with the power generation system. The linearly decreasing inertia weight particle swarm optimization algorithm is used to target the existing constraints and the distributed energy storage system's power balance requirements, state of energy constraints, power, and capacity constraints. Next, determine the most effective distributed energy storage system. Through simulation analysis, this method can improve the photovoltaic absorption capacity, reduce the number of actions of the energy storage system, and further increase the life of the energy storage system.

By reducing carbon dioxide emissions in the fields of transportation and industry, hydrogen generation from water electrolysis using renewable energy is a key technical avenue to attaining green and sustainable development. Renewable energy exhibits intermittent properties, with photovoltaic power exhibiting a relatively periodic output variation and wind power exhibiting a random fluctuation. The alkaline water electrolyzer and proton exchange membrane water electrolyzer performance and material degradation mechanisms under fluctuating power input are reviewed in this research. For the alkaline water electrolyzer, when the fluctuation power change is below the minute level, the electrolyzer cannot respond in time, thereby preventing the reaction balance and heat balance from being established, which may lead to the phenomenon of electrode catalyst dissolution and aggregation, diaphragm mechanical damage, electrolyte precipitation blocking reaction channel, etc., making the performance of the electrolytic cell decay. In a proton exchange membrane water electrolyzer, the fluctuation of power supply leads to the dissolution, migration, deposition, and aggregation of anode catalyst; the membrane degrades due to the attack of the local hot spot and hydroxyl free radical, and the dissolution and oxidation corrosion of the bipolar plate leads to the degradation of the electrolyzer performance. The ability of the electrolyzer to resist the fluctuation of power supply can be improved by studying mitigation strategies based on the influence rule of fluctuation on the operating condition, material, structure, and performance of the electrolyzer. This will increase the utilization rate of renewable energy, which is crucial to lowering the cost of hydrogen production from electrolytic water and promoting its widespread application.

Carbon dioxide energy storage (CES) technology is a new physical technology that is based on compressed air energy storage (CAES) and the Brayton power-generation cycle. It has high energy-storage density, long operation life, and compact-system equipment. In addition, it has good development and application prospects. This paper introduces the working principle and basic characteristics of a carbon dioxide energy-storage system and identifies the calculation method and evaluation effect of system round-trip efficiency (RTE) and energy storage density (ESD). The research status of thermoelectrical carbon dioxide energy storage (TE-CES), transcritical carbon dioxide energy storage (TC-CES), supercritical carbon dioxide energy storage (SC-CES), liquid carbon dioxide energy storage (LCES), and the carbon dioxide energy-storage system coupled with other energy systems are summarized by discussing recent relevant domestic and development processes of carbon dioxide energy-storage technology. In addition, the advantages, disadvantages, and adaptive application scenarios of different systems are identified. The research direction, key technologies, and main challenges of carbon dioxide energy storage are summarized. Finally, it identifies the development prospects of carbon dioxide energy storage in technology research and multiscenario application. Presently, a comprehensive analysis shows that the research on carbon dioxide energy-storage technology is mostly theoretical. We need to focus on system optimization design, experimental verification, and industrialized application. Carbon dioxide energy-storage technology is expected to obtain greater development space in the future power energy-storage market.

The quality of the electrode, as an important component of a lithium battery, is directly related to the electrochemical performance, safety, and service life of the battery. An electrode defect detection algorithm using topology filtering and an improved Canny operator is proposed to address the problems of uneven brightness of electrode images and low defect contrast. First, the filtering template using the topology principle is used to suppress the background noise of the image. To address the problem that the overall gray value of the image is too high, grayscale transformation is applied to correct the grayscale distribution of the image and enhance the image contrast. Second, an improved Canny operator is proposed, which uses bilateral filtering to prevent edge blurring and a multi-scale enhancement algorithm to improve uneven illumination and enhance image details. This is because the background has numerous fine textures and weak edge information. The four-directional Sobel operator is used to calculate the gradient magnitude and direction, which improves edge localization. The high and low thresholds are adaptively determined using the maximum entropy algorithm, avoiding the limitation of edge point determination and improving the effect of edge connection. The experimental research shows that, when compared with other algorithms, this algorithm can properly protect the edge details, accurately and completely extract defect contours (accurate and anti-noise), and has certain practical value.

To solve the problem of the low prediction accuracy of state of health (SOH) caused by the difficulty in extracting health factors of lithium-ion batteries, a feature-extraction algorithm of lithium-ion battery health factors based on the Douglas-Peucker fusion Min distance is proposed. The algorithm is used to extract the battery data feature under constant current and voltage charging, as well as constant power discharge strategies, to realize the SOH prediction of lithium batteries. First, the characteristic engineering is established for the measured experimental data, and the evaluation index is established using the Min distance. The battery health factor is extracted based on the Douglas-Peucker algorithm, and then the 34-dimensional health factor is obtained. For the extracted health factors, DBSO (difference-mutation brainstorm optimization) algorithm is used for optimization to eliminate irrelevant and redundant features, avoid overfitting of the model and improve model performance. Finally, the SVM (support vector machines) and its optimization model were used to predict the SOH of the battery. The experimental results show that the goodness of fit of the health factors extracted using feature engineering is greater than 0.96 in each SVM model. The DBSO-SVM model has the highest prediction accuracy and the best prediction effect, and the MSE (mean square error) value is less than 3. The proposed feature-extraction algorithm is verified on NASA data using different charging and discharging strategies; the results show that on the SVM model, the goodness of fit of B0005, B0006, and B0007 reaches 0.99, and the RMSE (root mean square error) values are lower than 6%. Compared with the various optimization algorithms, the DBSO-SVM model demonstrated the best performance.

The state of health (SOH) and the remaining useful life (RUL) of lithium-ion batteries for vehicles are key state parameters. Based on the charging process of electric vehicles, an improved Gaussian process regression (GPR) model for lithium battery SOH estimation and RUL prediction is proposed to achieve accurate estimation of SOH and RUL of the battery to ensure the safe and reliable operation of the vehicle. First, the maximal information coefficient (MIC) and Pearson coefficient are used to screen the multivariate information of the charging process as health factors. Further, the model structure is simplified using principal components analysis (PCA). The Gaussian process regression is then improved using particle swarm optimization and the combined kernel function. Finally, accurate online estimation of SOH and prediction of future RUL and SOH are realized. The validity of the model is verified with the NASA lithium-ion battery data set. This model outperforms other studies in terms of estimation and prediction accuracy. The maximum root mean square error (RMSE) of SOH estimation for test batteries is 0.0148, the maximum RMSE of SOH prediction is 0.0169, and the maximum absolute error of RUL prediction is 1 cycle.

The lithium battery state of charge (SOC) estimation technology is the core technology to ensure the reasonable application of electric energy storage and electric vehicles, as well as the control, operation, monitoring, and maintenance of lithium battery systems. It demonstrates the problems of nonlinearity, time variability, complexity, and uncertainty of influencing factors in the practical application of lithium batteries, thereby resulting in the difficulty, low accuracy, and insufficient adaptability of the state of charge estimation. As a result, numerous lithium battery state of charge estimation algorithms and improvement strategies have emerged. At the same time, some researchers have analyzed and compared the implementation methods, advantages, and disadvantages of various estimation methods, and improvement strategies, but the relevant review lacks a systematic summary and insufficient discussion on the technical characteristics and applicability of estimation methods. To begin, this paper examines the influencing factors and test standards of lithium battery state of charge estimation. Next, the traditional methods based on experimental calculation, filtering algorithms based on battery model, data-driven machine learning technology, and digital-analog hybrid estimation methods are compared and analyzed, as well as technical characteristics, implementation process, applicable conditions, problems, pain points, and application advantages. The research focus and application status of the existing state of charge estimation technology for lithium batteries are systematically and comprehensively discussed. Finally, future research directions for lithium battery state of charge estimation algorithms are proposed.

Performance degradation due to battery aging highly depends on the charge handling capacity. It is essential to identify battery performance degradation parameters efficiently and accurately such that the prediction performance of battery service life can be improved. However, due to the large population size and more expected iterations, the current parameter identification approaches for the battery performance degradation model are still severely constrained. As a result, it is not conducive to improving the applicability of online parameter identification and update. Aiming at solving this problem, a parameter identification method based on self-adaptive synergistic guidance is proposed for the battery performance degradation model in this paper. To achieve the initial-stage global distribution of population individuals in the parameter searching space, a complete compromise between population variety and population fitness is first considered based on the adaptive synergistic method. Based on this, the population individuals search locally around the global elite individuals during the elite guiding, aiming to quickly converge to the global optimal solution in the later stage. The verification results based on the measured datasets show that the parameter identification efficiency and accuracy for the battery pack performance degradation model can be obviously improved by the proposed method in the case of small population size. For the capacity fade model and power fade model, 0.237% and 0.37% fitness values within 0.6 s and 1.1 s can be achieved, respectively. In fact, the identification efficiency is improved by 81.35% and the mean fitness is reduced by 3.8% compared with Ant Lion Optimizer, while the identification efficiency is improved by 17.14% and the mean fitness is reduced by 22.11% compared with Grey Wolf Optimizer.

Using early data to accurately predict the remaining service life (RUL) of a battery can accelerate the improvement and optimization of the battery. However, the battery degradation process is nonlinear, and the capacity attenuation can be neglected in the early stage, which makes the RUL prediction challenging. To solve this problem, this paper uses the early cycle data of batteries, and constructs a hybrid prediction model of the WOA algorithm and the XGBoost algorithm to predict RUL. In this study, the experimental data of batteries are preprocessed, and the changes in discharge voltage-capacity degradation curve and capacity increment curve are observed. Then, the potential characteristics with high a correlation as well as actual capacity state are selected, and the time series data are used as the input of the XGBoost prediction model. Then, the parameters of the model are optimized by the WOA algorithm. Finally, 84 battery data provided by Toyota Research Institute using multi-step charging and constant current discharging are used to verify the model. The results show that the proposed model can predict the whole battery life only using the data of the first 100 cycles, and the test error is 4%.

Ionic conductivity is an important parameter in the evaluation of lithium-ion battery electrolyte performance. Ionic conductivity affects the low temperature and rate capability of the battery and provides guiding principles for electrolyte design. Traditional research and development methodologies are primarily based on trial and error, which involves many variables. This results in high experimental costs and a long discovery cycle. To solve the above issues, a conductivity optimization design method that combines a space filling mixture design and Gaussian process regression is proposed in this paper. According to the formulation parameters of the electrolyte, including different types of cyclic carbonate (ethylene carbonate), linear carbonates, and carboxylic acids as the model's input, the ionic conductivity is output by the model, and the maximum likelihood estimation is employed to solve the super parameters. The effectiveness and precision of the proposed model were verified in subsequent experiments, and we found that an electrolyte solvent recipe that satisfies any conductivity requirements can be predicted.

The resistance and capacitance of supercapacitors are not constant; they are affected by frequency and other factors. we realized that the fractional-order equivalent electrical-circuit models (ECMs) can describe the nonlinear characteristics of supercapacitors more accurately. To address the problem of solving the parameters of the fractional-order models (FOMs), a parameter-identification method based on frequency-band divisions is proposed. Based on the impedance characteristics of supercapacitors in different frequency bands, the equivalent impedance expressions at corresponding frequency bands are proposed. We found the unknown parameters in the impedance expressions at each frequency band using the impedance data at typical frequencies. Thus, the parameter identification of FOMs of supercapacitors in full-band is realized. This method reduces the FOM parameter identification difficulty. Finally, the dynamic-stress test (DST) and constant-current charge-discharge experiments at different frequencies are conducted on the supercapacitors. The output voltages of the solved FOMs are compared with the measured voltages of supercapacitors under DST. The results show that the mean relative error of the FOMs is 1.52%, and the maximum relative error is limited to 4%. Under the constant-current charge-discharge experiments, the maximum relative error is limited to 6%. The proposed method has high effectiveness and accuracy.

A hierarchical voltage sag mitigation scheme based on user-side energy storage systems (UESS) was proposed for premium power parks to improve the economic benefits of UESS located in industrial parks, in addition to improving the peak-shaving and valley-filling function of UESS, and economic analysis was conducted. First, the topology and control strategy of UESS were designed so that the UESS could perform the voltage sag mitigation function in addition to the conventional peak-shaving and valley-filling function. A hierarchical voltage sag mitigation scheme based on the coordination of UESS and dynamic voltage restorer (DVR) was proposed to avoid the possible negative impacts of switching between different control modes of UESS. In this scheme, the lowest power supply level does not contain any voltage sag compensation equipment. The medium level of power supply is provided by a single device, while the highest level of power supply is ensured by coordinating UESS and DVR. The effectiveness of the proposed hierarchical power supply scheme was verified by simulations conducted in PSCAD/EMTDC. Finally, the cost and benefit model of UESS was established, and economic analysis of the proposed hierarchical power supply scheme was conducted by comparing the conventional peak-shaving and valley-filling type UESS, demonstrating that the proposed scheme can significantly improve the economic benefit and shorten the payback period of UESS for users suffering from voltage sag.

The development of hydrogen refueling stations (HRS) technology is an important support in the application of low-carbon clean hydrogen in the field of transportation. This article reviews the technology of HRS, introduces the roadmap and technical targets in the United States, Japan, Europe, and other countries, analyzes the development status of domestic HRS technology, and refines three key cost-reduction technology development ideas and objectives: reducing equipment cost, improving operational reliability, and reducing operation energy consumption. Many countries have carried out research and development layouts through the localization of core equipment, key materials, and components, such as high reliability and high-efficiency hydrogen compressors and liquid hydrogen pumps, high-efficiency hydrogenation machines, high-pressure valves, and long-life diaphragms, to reduce the overall cost of hydrogenation stations, which are an important reference value for developing hydrogenation technology routes in China. Based on the development status of domestic hydrogenation infrastructure technology, this study analyzed and quantified the gap between China's key technology and equipment performance indicators and foreign countries. This paper proposes a technical route for the whole station and critical technical equipment of China's hydrogenation infrastructure and suggests concerted efforts from the aspects of technological breakthrough, policy encouragement, and industrial collaborative innovation. The overall aim was to reduce the cost of hydrogenation infrastructure to fully exploit the role of hydrogen energy in the deep decarbonization of transportation.

The global hydrogen energy industry has entered a new era of rapid industrialization. More than 20 major economies, such as Europe, the United States, Japan, and South Korea, have elevated the development of hydrogen energy to the national strategic level and have successively formulated development plans, roadmaps, and related support policies to accelerate industrialization. This paper analyzes and summarizes the hydrogen development strategies of Japan, Germany, South Korea, the United States, and Australia and refines the three core driving forces for hydrogen development: deep decarbonization, ensuring energy security, and achieving economic growth. The trends of hydrogen development orientation, hydrogen source structure transition, hydrogen application scenarios, and industrial development stages are obtained based on the international consensus on the goal of carbon neutrality and the disruption of global geopolitics. Major countries consider overall resource endowment, technology and industrial base, market demand, and other factors, and promote hydrogen technology research and industrialization development using local conditions, which has important reference value for China's high quality hydrogen industry. This paper proposes three approaches to implementing the "Medium and Long-Term Development Plan for Hydrogen Energy Industry Development (2021-2035)": strengthening national level hydrogen energy strategy guidance; increasing key core technology research efforts; and accelerating the demonstration and application of diverse scenarios.