Usable Capacity Research Articles

Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell

Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies help to better understand and model degradation and to optimize the operating strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications. To our knowledge, the dataset1 presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to cells. The dataset1 includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution). The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operating strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.

Dual‐inertia flywheel energy storage system for electric vehicles

AbstractManaging the high‐rate‐power transients of Electric Vehicles (EVs) in a drive cycle is of great importance from the battery health and drive range aspects. This can be achieved by high power‐density storage, such as a high‐speed Flywheel Energy Storage System (FESS). It is shown that a variable‐mass flywheel can effectively utilise the FESS useable capacity in most transients close to optimal. Novel variable capacities FESS is proposed by introducing Dual‐Inertia FESS (DIFESS) for EVs. The feasibility of the proposed concept is evaluated by deriving the size of a Single‐Inertia FESS (SIFESS) for a battery EV, which runs the well‐known Urban Dynamometer Driving Schedule. The sizing framework consists of an Energy Management System using the constrained Pontryagin's minimum principle and a proposed sizing algorithm. Then, by splitting the derived SIFESS inertia into two separate inertias, the appropriate engaging control of inertias is determined for some driving cycles including, the Artemis Urban, Braunschweig City, and Worldwide Harmonised Light‐duty Vehicles Test Cycle. The dual inertias suitable sizes are derived using a proposed algorithm, which targets maximising the FESS useable capacity. The results show that compared to the SIFESS, the DIFESS can employ the FESS's useable capacity more effectively.

A novel active cell balancing topology for serially connected Li-ion cells in the battery pack for electric vehicle applications

In a Battery Management System (BMS), cell balancing plays an essential role in mitigating inconsistencies of state of charge (SoCs) in lithium-ion (Li-ion) cells in a battery stack. If the cells are not properly balanced, the weakest Li-ion cell will always be the one limiting the usable capacity of battery pack. Different cell balancing strategies have been proposed to balance the non-uniform SoC of cells in serially connected string. However, balancing efficiency and slow SoC convergence remain key issues in cell balancing methods. Aiming to alleviate these challenges, in this paper, a hybrid duty cycle balancing (H-DCB) technique is proposed, which combines the duty cycle balancing (DCB) and cell-to-pack (CTP) balancing methods. The integration of an H-bridge circuit is introduced to bypass the selected cells and enhance the controlling as well as monitoring of individual cell. Subsequently, a DC–DC converter is utilized to perform CTP balancing in the H-DCB topology, efficiently transferring energy from the selected cell to/from the battery pack, resulting in a reduction in balancing time. To verify the effectiveness of the proposed method, the battery pack of 96 series-connected cells evenly distributed in ten modules is designed in MATLAB/Simulink software for both charging and discharging operation, and the results show that the proposed H-DCB method has a faster equalization speed 6.0 h as compared to the conventional DCB method 9.2 h during charging phase. Additionally, a pack of four Li-ion cells connected in series is used in the experiment setup for the validation of the proposed H-DCB method during discharging operation. The results of the hardware experiment indicate that the SoC convergence is achieved at ~ 400 s.

Capacity building in porous materials research for sustainable energy applications.

The project aimed to develop porous materials for sustainable energy applications, namely, hydrogen storage, and valorization of biomass to renewable fuels. At the core of the project was a training programme for Africa-based researchers in (i) the exploitation of renewable locally available raw materials; (ii) the use of advanced state-of-the-art techniques for the design and synthesis of porous materials (zeolites and metal-organic frameworks (MOFs)) for energy storage; and (iii) the valorization of sustainable low-value feedstock to renewable fuels. We found that compaction of the UiO-66 MOF at high pressure improves volumetric hydrogen storage capacity without any loss in gravimetric uptake, and experimentally demonstrated the temperature-dependent dynamic behaviour of UiO-66, which allowed us to propose an activation temperature of ≤ 150°C for UiO-66. Co-pelletization was used to fabricate UiO-66/nanofibre monoliths as hierarchical porous materials with enhanced usable (i.e. deliverable) hydrogen storage capacity. We clarified the use of naturally occurring kaolin as a source of silica and alumina species for zeolite synthesis. The kaolin-derived zeolite X was successfully used as a catalyst for the transesterification of Jatropha curcas oil (from non-edible biomass) to biodiesel. We also prepared porous composites (i.e. carbon/UiO-66, organoclay/UiO-66 and zeolite/carbon) that were successfully applied in electrochemical sensing.

A Review of Thermal Management and Heat Transfer of Lithium-Ion Batteries

With the increasing demand for renewable energy worldwide, lithium-ion batteries are a major candidate for the energy shift due to their superior capabilities. However, the heat generated by these batteries during their operation can lead to serious safety issues and even fires and explosions if not managed effectively. Lithium-ion batteries also suffer from significant performance degradation at low temperatures, including reduced power output, a shorter cycle life, and reduced usable capacity. Deploying an effective battery thermal management system (BTMS) is crucial to address these obstacles and maintain stable battery operation within a safe temperature range. In this study, we review recent developments in the thermal management and heat transfer of Li-ion batteries to offer more effective, secure, and cost-effective solutions. We evaluate different technologies in BTMSs, such as air cooling, liquid cooling, phase change materials, heat pipes, external preheating, and internal preheating, discussing their advantages and disadvantages. Through comparative analyses of high-temperature cooling and low-temperature preheating, we highlight the research trends to inspire future researchers. According to the review of the literature, submerged liquid BTMS configurations show the greatest potential as a research focus to enhance thermal regulation in Li-ion batteries. In addition, there is considerable research potential in the innovation of air-based BTMSs, the optimization of liquid-based BTMSs, the coupling of heat pipes with PCMs, the integration of PCMs and liquid-cooled hybrid BTMSs, and the application of machine learning and topology optimization in BTMS design. The application of 3D printing in lithium-ion battery thermal management promises to enhance heat transfer efficiency and system adaptability through the design of innovative materials and structures, thereby improving the battery’s performance and safety.

Sorghum landraces perform better than a commonly used cultivar under terminal drought, especially on sandy soil

Landraces of sorghum [Sorghum bicolor (L.) Moench] have a high potential for drought adaptations to increasingly extreme climates. We investigated the performance of five sorghum genotypes (four landraces and one commonly grown elite line) under water-limited conditions. Plants were grown until maturity in field-like columns on soils of four textures (silty clay, sandy loam, loamy sand, sand), which were dried during flowering stage down to 30 % usable field capacity. Plant transpiration, physiological characteristics, and yield were measured. For most of the measured parameters, the interaction between genotypes and soils was statistically significant. Alongside the gradient in available water between soils, plants had the highest total transpiration, transpiration efficiency (TE), harvest index (HI), and nutrient uptake in silty clay, steadily reduced towards soils with higher sand content. Especially in sandy soil, all measured plant performance parameters were significantly reduced compared to the other soils. There was a significant negative relationship between later flowering time and HI. While the elite cultivar M35–1 showed the highest TE, it suffered from late flowering and yield loss on all soils, especially when growing on sandy soil. The landraces IS 29914 and IS 8348 had a stable HI irrespective of their lowest TE. The shorter the plant, the better it coped with water and nutrient limitation and high transpiration efficiency was not connected to water conservation. The study overall emphasizes the high potential of sorghum landraces to overcome more extreme droughts as imposed by climate change. It also underlines the importance and strong interaction effect of soil texture on plant performance and transpiration efficiency, which is crucial to be considered in crop production. This outlines that specifically regions with sandy soils, characterized by low water-holding capacities, need genotypes that efficiently utilize the limited available water and nutrient resources – a genetic potential hidden in many landraces.

Reinforcement learning for battery energy management: A new balancing approach for Li-ion battery packs

This study investigates the challenge of cell balancing in battery management systems (BMS) for lithium-ion batteries. Effective cell balancing is crucial for maximizing the usable capacity and lifespan of battery packs, which is essential for the widespread adoption of electric vehicles and the reduction of greenhouse gas emissions. A novel deep reinforcement learning (deep RL) approach is proposed for passive balancing with switched shunt resistors. Notable deep RL algorithms capable of handling discrete actions, such as Trust Region Policy Optimization (TRPO), Proximal Policy Optimization (PPO), Deep Q-Network (DQN), Augmented Random Search (ARS), and Asynchronous Advantage Actor Critic (A3C), are investigated. TRPO demonstrates superior performance compared to other deep RL algorithms and rule-based methods in both charging and discharging scenarios without requiring fine-tuning, optimizing the balance between cell balancing and switch changes. It achieves up to 16.8% improvement in battery pack capacity, 69.4% reduction in state-of-charge variance among cells, and 40.4% decrease in the number of switching operations in simulation results for five li-ion cells connected in series.The study introduces an innovative application of deep RL for passive balancing, a comprehensive battery cell modeling technique, and a tailored multi-objective reward function that balances cell balancing and switching costs. This work represents a significant advancement in applying deep RL to battery management systems, providing a framework for further research and practical implementation in energy storage systems.

Experiment-supported survey of inefficient electrolyte mixing and capacity loss in vanadium flow battery tanks

This study investigates the impact of electrolyte mixing inside the tanks of Vanadium Flow Battery (VFB) on capacity degradation. Heterogeneous mixing inside the tanks may lead to a severe capacity drop due to the existence of stagnant electrolyte regions and asymmetries in the State of Charge (SoC) of the positive and negative electrolytes reaching the cell. The study is based on a preliminary order-of-magnitude analysis involving the dimensionless Richardson and Reynolds numbers. A subsequent experimental campaign is carried out in which cell voltage and current response are screened for different tank designs and operating conditions to identify different fluid-dynamics events in the tanks. The results highlight the two main competing phenomena affecting the electrolyte fluid dynamics: buoyancy effects induced by density variations, and the inertia of the inlet submerged jet. The interplay between these two forces determines the flow field and therefore the SoC of the electrolyte feed to the cell, which affects the usable capacity and battery performance. Inertia dominated flows induce homogeneous electrolyte mixing, leading to a higher usable capacity, whereas buoyancy dominated flows result in a lower one. Furthermore, various inner structures were tested within the tanks to optimize mixing. These structures were created using additive manufacturing techniques. The implementation of helicoidal geometries within the tanks, promoting longer electrolyte paths and ample cross-sectional areas for convective mixing, markedly enhanced battery capacity compared to traditional empty tanks. These findings call for further investigation into optimizing the geometry of large-scale (VFB) storage tanks.

Sorption properties of nanostructured ball-milled porous silicon for solid-state hydrogen storage up to 80 bar

Solid-state storage is a feasible solution to store hydrogen compared to commercially available techniques. The disadvantage of using metal and complex hydrides for storage is the elevated temperature operation (>400 °C) and slow reaction kinetics. Porous materials like carbon nanostructures, metal-organic frameworks, zeolites, and porous polymers possess high surface energy and hydrogen affinity. However, cryogenic temperature operation and low storage at ambient conditions are major limitations for practical storage applications. Modifying the material morphology and storage parameters to enhance hydrogen storage is under intense investigation. This study focuses on nanostructuring porous silicon (PS), evaluating its structural characteristics, and investigating its ability to store hydrogen at up to 80 bar. The challenges of large particle size and low-pressure hydrogen storage in the novel porous material is addressed with possible mechanisms. The discussion explored the potential of utilizing interconnected pores via nanoscale engineering and increased charging pressure to optimize hydrogen exposure. Nanostructuring the hand-grinded porous Si (HGPS) reduces crystallite size, boosts surface energy and enhances thermodynamics. At 80 bar and 120 °C, the ball-milled PS (BMPS) exhibits a hydrogen storage capacity of 10.7 wt%. The isosteric heat of adsorption is utilized to optimize storage conditions to achieve useable capacity. The hydrogen adsorption pressure is optimized between 40 and 60 bar, where the storage capacity ranges from 2 wt% and 6 wt% (meeting the hydrogen storage target set by the US Department of Energy). X-ray Photoelectron Spectroscopy investigates surface states and bonding involving silicon hydrides. The effect of nanostructuring on decomposition energy is observed by differential scanning calorimetry. The decreased crystallite size, examined through X-ray diffraction and Raman spectroscopy, exposes nanopores accessible to hydrogen. The accessibility enhances storage capacity in free and surface-affixed states, rendering BMPS for reversible storage applications. The lower temperature requirement for hydrogen adsorption and release from storage material aligns with Sustainable Development Goal 7 (SDG 7) on affordable and clean energy.

Long term performance evaluation of a commercial vanadium flow battery system

This paper describes the results of a performance review of a 10 kW/100 kWh commercial VFB system that has been commissioned and in operation for more than a decade. The evaluation focused on the system efficiencies, useable capacity, electrolyte stability and stack degradation. The analysis shows that the system has stable performance and very little capacity loss for over a decade since commissioning. Only very recently, a slight decrease in system discharge capacity (approximately 5 %) was observed and indicated by changes in the electrolyte valence state. The capacity was restored to the original level after conducting a rebalancing procedure. This demonstrates the advantage that the flow batteries employing vanadium chemistry have a very long cycle life. Furthermore, electrochemical impedance spectroscopy analysis was conducted on two of the battery stacks. Some degradation was observed in one of the stacks reflected by the increased charge transfer resistance. To further investigate the ageing of the stacks, reverse polarity tests were carried out. It is found that reversing the polarity both hydraulically and electrically can restore the stack performance. The study shows that the VFB is a reliable technology for large-scale energy storage applications.

Research on the heating effect evaluation of the electromagnetic induction heating system at low temperature based on the electrochemical-thermal coupling model

The extremely fast electromagnetic induction heating system (EIHS) was recently introduced to improve the poor charge and discharge performance of lithium-ion batteries (LiBs) at low temperature. In this work, aimed to investigate the heating effect of EIHS, the accurate electrochemical-thermal coupling model, validated against the charging capacity calibration with various C-rates and HPPC tests at different environments, was developed in depth to reflect the electrochemical and heat transfer behaviors of the LiB exposed to external cool air during the electromagnetic induction heating process. When the copper coil was subjected to a sinusoidal alternating current (SAC) excitation at 10 A, 3 kHz, the LiB can be warmed up to 293.15 K from 243.15 K within 742 s with an even heat generation inside the LiB. The impact of the SAC parameters on the needed heating time was illustrated with time maps, a series of contours suggested that the heating velocity increase with the increase of both the amplitude and frequency. As compared with the low-temperature state, the internal resistance had a more than 3-fold decrease, which can improve the discharging voltage platform and terminal voltage output, thus increasing the pulse power and usable capacity. Neither noticeable capacity retention difference before and after the heating cycles nor obvious capacity loss discrepancy between the normal charge-discharge and heating cycle tests was found at the end of the 200 heating cycles, so the EIHS can achieve a good tradeoff among temperature rising effect, working behaviors and LiB cycle lifespan, which had a considerable potential to enhance the applicability of EVs (electric vehicles) in frigid weather. Moreover, a better heat transfer condition, higher material thermal conductivity and lower specific heat capacity play an important positive role on the improvement of temperature rising performance.

Modeling the impact of extreme summer drought on conventional and renewable generation capacity: Methods and a case study on the Eastern U.S. power system

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation’s energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events.

An intelligent active equalization control strategy based on deep reinforcement learning for Lithium-ion battery pack

The inconsistency in large-scale series-connected lithium battery pack significantly impacts the usable capacity of the battery pack and raises the likelihood of safety risks. In this paper, an equalizer based on Buck–Boost converter is utilized. This equalizer comprises a pulse width modulation (PWM) controlled Buck–Boost equalization circuit and a switch array. In order to maximize the performance of the equalizer, this paper proposes an equalization strategy based on reinforcement learning algorithm to reduce the equalization time. Under the simulation environment of MATLAB/Simulink, the equalization experiments under different working conditions are designed. Compared to the mean-difference algorithm, the proposed algorithm based on deep reinforcement learning has up to 46% improvements on balancing speed, demonstrating the feasibility and effectiveness of the balancing scheme.

Battery health prediction using two-dimensional multi-channel ensemble models

The accurate assessment of battery health is crucial for maximizing the performance and lifespan of lithium-ion batteries. In this paper, an ensemble model based on a two-dimensional multi-channel convolutional neural network is proposed to predict the maximum usable capacity of lithium-ion batteries. First, based on the charge–discharge process, the characteristic-derived lines of the capacity–voltage (Q–V) curve are extracted. Next, the Gramian angular summation field (GASF) is employed to convert one-dimensional time series data into image matrices, with the aim of preserving temporal characteristics. Finally, the paper discusses the impact of 2D matrix size on prediction results and introduces the use of a 2D multi-channel ensemble model for the unsupervised recognition and extraction of battery decline information from images, marking the first time this approach has been utilized. The experimental results demonstrate that the proposed method effectively captures battery degradation patterns from multiple perspectives. The average mean absolute percentage error of 1.95% and root mean square error of 1.41% on the verified batteries indicate the robustness and generalizability of the approach.

Li-decorated BC3 nanopores: Promising materials for hydrogen storage

In the quest of new absorbent for hydrogen storage, we investigate the capacities of slit pores formed by two BC3 sheets decorated with Li atoms. Their hydrogen storage capacities are determined using density-functional theory in conjunction with a quantum-thermodynamic model that allows to simulate real operating conditions, i.e., finite temperatures and different loading and depletion pressures applied to the adsorbent in the charge-delivery cycles. We show that the capacities of the adsorbed hydrogen phase of Li-decorated BC3 slit pores are larger than those reported recently for graphene and Li-decorated borophene slit pores. On the other hand, the usable volumetric and gravimetric capacities of Li-decorated BC3 slit pores can meet the targets stipulated by the U.S. Department of Energy (DOE) for onboard hydrogen storage at moderate temperatures and loading pressures well below those used in the tanks employed in current technology. In particular, the usable volumetric capacity for pore widths of about 10 Å meets the DOE target at a loading pressure of 6.6 MPa when depleting at ambient pressure. Our results highlight the important role played by the rotational degree of freedom of the H2 molecule in determining the confining potential within the slip pores and their hydrogen storage capacities.

Method for determining the parameter values of a hydrogen power plant with a fuel cell element based on vehicle telemetry data

The article presents a method for determining the values of operational parameters of a power system with a fuel cell (PSFC) and a rechargeable battery, taking into account the actual operating modes of a hybrid electric vehicle, taking into account the requirements for autonomy (reserve) and energy recovery mode. In the process of numerical research of the telemetry data of the main truck KAMAZ-54901, it was determined that the usable capacity of the PSFC corresponds to 138.3 kW, and the required energy intensity of the rechargeable energy storage system is 38.28 kWh at an average speed of 80.8 km/h. Keywords hydrogen fuel cell; hydrogen fuel reserve; compressed hydrogen storage system; battery charge; hybrid power plant

Unlocking the Potential of Li–Ag Alloys: Phase Selection and Practical Application

Dendrite formation, contact loss, and continuous formation of the solid electrolyte interphase (SEI) preclude the practical use of the energy-dense lithium (Li) metal. Li–Ag alloys have the potential to address these issues due to their exceptional lithiophilicity, outstanding mechanical stability, and moderate chemical stability. This study evaluates all phases in the Li–Ag phase diagram based on lithiation capacity, Li insertion, mechanical property, and chemical stability. Our findings suggest that Li 4 Ag is the most promising phase, and the Gibbs free energy of nucleation (∆ G nucle ) for Li–Ag alloys is 3 to 5 orders of magnitude smaller compared to pure Li, resulting in uniform nucleation and deposition behavior. We proposed practical applications within the Li 4 Ag phases or from the Li 9 Ag 4 to the Li 4 Ag phases, which may provide a usable capacity of 409 to 696 mAh/g, respectively. Experiments indicate that Li 4 Ag exhibits not only the smallest impedance but also the highest capacity retention compared to Li 9 Ag 4 and pure Li. The study provides valuable guidance for the selection and application of Li-containing alloys in future battery development.

A Ni/Co-free high-entropy layered cathode with suppressed phase transition and near-zero strain for high-voltage sodium-ion batteries

High-entropy layered oxides have emerged as a new class of cathode materials for sodium-ion batteries by providing infinite possibilities to tailor energy storage capabilities. However, owing to the lack of advanced high-entropy layered material, the influence of configurational entropy/compositional disorder on the high-voltage electrochemical performance of sodium-based layered cathode has seldom been explored. In this work, a Ni/Co-free high-entropy layered oxide P2-Na0.65Mn0.65Cu0.2Li0.06Mg0.015Ti0.015Al0.015Zr0.015Y0.015La0.015O2 (Mn-Cu-HEO) was prepared by stirring hydrothermal method, and investigated as a new cathode material for sodium-ion batteries. It is found that high configurational entropy and strong M−O configurations (M = Ti, Al, Zr, Y, and La) greatly stabilize the layered framework structure and MnO6 octahedral local structure, restraining the deleterious phase transition and large volume change during high-voltage cycling, thus resulting in high reversible cationic/anionic redox. In the meantime, disordered atomic arrangement in transition metal layer efficaciously mitigates Na+/vacancy ordering during de-/sodiation, enhancing the Na+ transport kinetics. Benefiting from the high-entropy stabilization effect, complex atomic arrangement, and multielemental composition, Mn-Cu-HEO displays splendid cyclic stability (87.2 % capacity retention after 500 cycles, very small change in cell volume (0.53 %) after 100 cycles), excellent rate capability (55.5 mAh g−1 at 10C), and a usable reversible capacity of 85.1 mAh g−1 at 1C in high-voltage range of 2.0–4.5 V. This work expands the horizons of high-entropy layered materials, providing new insight in the design and construction of highly stable and high-voltage sodium ion host.

Exploring the hydrogen and methane storage capacities of novel DUT MOFs at room temperature: A Grand Canonical Monte Carlo simulation study

Metal-Organic Frameworks (MOFs) are a significant and promising category of solid that have garnered substantial attention for their potential in storing hydrogen and methane. Grand Canonical Monte Carlo (GCMC) simulations of the usable hydrogen and methane storage capacities of five DUT MOFs (Dresden University of Technology), based on tritopic ligands and copper, have been carried out at room temperature and pressures between 0.5 and 35 MPa. These DUT MOFs exhibit high usable hydrogen and methane storage capacities, comparable or higher than the storage capacities of the best classical MOFs and the best Cu-based MOFs. The usable methane gravimetric storage capacities at 35 MPa and room temperature of these DUTs reach the Department of Energy (DOE) methane gravimetric target and their usable volumetric capacities are close to the DOE methane volumetric target.

High-capacity hydrogen storage in lithium decorated penta-BN2: A first-principles study

The development of solid hydrogen storage materials is an important part of the large-scale application of hydrogen energy. The gravimetric density of hydrogen storage materials and modified metal atoms agglomeration are the key research issues in two-dimensional hydrogen storage materials. Based on first-principles calculations, lithium-modified penta-BN2(P-BN2) is developed as a new hydrogen storage material. The geometric and electronic structures of lithium-modified P-BN2 (Li-P-BN2) have been calculated. P-BN2 has strong binding ability to lithium metal atoms, preventing the formation of lithium metal clusters, and the material has a strong stability. Twenty-eight hydrogen molecules can be stably adsorbed by the Li-P-BN2 system, and the theoretical storage gravimetric density of hydrogen is 13.27 wt%. Ab initio molecular dynamics (AIMD) shows that the material has a useable capacity of 8.95 wt% at 300 K. The mean desorption temperature is 437.13 K. The excellent hydrogen adsorption capacity and high gravimetric density of Li-P-BN2 may make it a promising hydrogen storage material.