Discharge Capacity Of Battery Research Articles

Unique flake-shaped sulfur morphology favored by the binder-free electrophoretically deposited TiO2 layer as a promising cathode structure for Li-S batteries

Metal oxides have been extensively studied as catalyst additives in Li-S batteries due to their high affinity for soluble lithium polysulfides. The present study developed a novel carbon nanomaterials- and binder-free 3D sulfur host by electrophoretic deposition (EPD) of TiO2 nanoparticles on carbon fiber paper (CFP). Benefiting from the unique well-connected TiO2 porous layer formed by EPD, the initial discharge capacity of Li-S battery was increased from 1160 mAh g-1 in conventional casted TiO2/binder/S cathode (Cast:CFP/PVDF/TiO2/S) to 1310 mAh g-1 in the EPD:CFP/TiO2/S cathode, along with an overpotential drop of 16%. Unlike typical sulfur particulates found in the Cast:CFP/PVDF/TiO2/S samples, flake-shaped sulfur precipitates were observed in the binder-free EPD:CFP/TiO2/S electrode at the end of charge. Pulverization of sulfur was effectively suppressed in the EPD:CFP/TiO2/S electrode owing to the formation of the flake-shaped sulfur morphology, leading to superior electrochemical performance and better cycle life. Microstructural studies and real-time EIS investigations revealed that sulfur flakes nucleated across the Li2S matrix at the initial stages of charge and grew vertically from the sulfur/TiO2 interface. The preferential growth mechanism of sulfur flakes was attributed to the surface conductance of the EPD-TiO2 film along the ordered clusters formed during EPD, enhancing the kinetics of electrocatalytic reactions of polysulfides at the TiO2/sulfur interface. Our results show that developing novel methods to modify the morphology of secondary sulfur upon cycling is critical for enhancing charge-discharge performance in Li-S batteries.

Enhanced electrochemical stability and ion transfer rate: A polymer/ceramic composite electrolyte for high-performance all-solid-state lithium-sulfur batteries

All-solid-state (ASS) lithium-sulfur (LiS) batteries utilizing composite polymer electrolytes (CPEs) represent a promising avenue in the domain of electric vehicles and large-scale energy storage systems, leveraging the combined benefits of polymer electrolytes (PEs) and ceramic electrolytes (CEs). However, the inherent weak interface compatibility between PEs and CEs often leads to phase separation, thereby impeding the transposition of Li+. In this study, the trimethoxy-[3-(2-methoxyethoxy)propyl]silane (TM-MES) is introduced as a chemical agent to form bonds with polyethylene oxide (PEO) and Li10GeP2S12 (LGPS), resulting in the development of a novel composite polymer electrolyte (CPETM-MES). This innovative approach mitigates phase separation between PEs and CEs while concurrently enhancing the protective capabilities of LGPS against decomposition at the interfaces of both the Li anode and sulfur cathode. Moreover, the CPETM-MES exhibits superior mechanical toughness, an expanded electrochemical window, and elevated ionic conductivity. In the symmetric cell, it demonstrates an extended operational lifespan exceeding 1800 h, and the current density can reach up to 1.05 mA/cm2. Furthermore, the initial discharge capacity of ASS LiS batteries utilizing CPETM-MES attains 1227 mAh/g and maintains a capacity of 904 mAh/g after 100 cycles. Notably, a high-energy-density of 2454 Wh/kg is achieved based on the sulfur cathode.

A multi-step discharge/charge model of Li[sbnd]O2 batteries coupled with electrolyte decomposition and carbon electrode corrosion reactions

Electrolyte decomposition and electrode corrosion stand as two primary side reactions in lithium‑oxygen (LiO2) batteries during their discharge/charge cycles. In this work, a comprehensive LiO2 battery model combining multi-step lithium peroxide (Li2O2) formation, electrolyte decomposition, and electrode corrosion is proposed. Based on this model, the deposition behaviors and cycling performance of the LiO2 battery under deep discharge/charge cycles are investigated. The stop of discharge is mainly ascribed to the loss of active surface area for the battery using tetraethylene glycol dimethyl ether (TEGDME) electrolyte, while both O2 transport limitation and active surface area loss lead to the discharge termination for battery using dimethyl sulfoxide (DMSO) electrolyte. The incomplete decomposition of Li2O2 and lithium carbonate (Li2CO3) clogs electrode pores, leading to a continuous decline in the discharge capacity of the LiO2 battery. For the TEGDME-based battery, the undecomposed Li2CO3 gradually dominates the deposition with cycles, wherein electrode corrosion becomes the primary source of the undecomposed Li2CO3 after 3 cycles. For the DMSO-based battery, undecomposed Li2O2 is always a dominant trigger for battery discharge capacity degradation, although electrode corrosion remains a key contributor to Li2CO3 generation. Despite the DMSO-based battery exhibiting lower rates of electrolyte decomposition and electrode corrosion, it demonstrates poorer cyclic performance than the TEGDME-based battery due to the generation of more toroidal Li2O2. Moreover, when the charging cut-off voltage is reduced to 4.2 V, discharge capacity diminishes more rapidly due to the increased accumulation of undecomposed Li2O2, despite suppressed Li2CO3 deposition. Finally, the results confirm that thick electrodes lead to deteriorating cycling performance, stemming from increased discharge/charge overpotential and extended discharge/charge times, thus intensifying the side reactions.

Fundamental Studies of Discharge Mechanism and Capacity Limits of Lead Acid Battery Electrodes

Long-duration energy storage provides key benefits such as consistent power supply during periods of high demand for grid reliability and flexibility. For environmental benefits, it allows for more renewable energy integration and helps reduce reliance on fossil fuels to lower greenhouse gas emission. Lead batteries have the economic potential to continue serving as an important energy storage technology for a decarbonized sustainable energy future given they are earth-abundant, inexpensive, and 99% recyclable. Advancing the design of lead batteries with higher material utilization, fast recharge rates, and long-cycle life requires a fundamental understanding of the electrochemical and chemical processes taking place at the atomic and molecular scales. In this work, we will discuss how the use of well-defined electrode interfaces allows us to gain insights into the fundamental limits of discharge capacity and recharge rates. We were able to unveil the relationships between discharge rates and PbSO4 particle size/layer thickness that ultimately governs the maximum discharge capacity accessible as a function of discharge rate on both the negative and positive lead electrodes. This data helped us develop a mathematical model that captures the key processes concerning lead ion and (bi)sulfate ion gradients coupled to nucleation and growth that explain, from first principles, the origin of the well-known empirical Peukert law. In this context, exploring how variables such as acid concentration, temperature, and the presence of lignosulfonate additives in the electrolyte further influence discharge capacity allows us to understand how thermodynamic, kinetic, and even mass transport play a huge role in governing the accessible capacity from the electrodes. This study paves the way for a deeper understanding of the variables that are most important in improving the discharge capacity of lead-acid batteries, and thus batteries that can be utilized at their full potential.

Comparison of prediction performance of lithium titanate oxide battery discharge capacity with machine learning methods

Comparison of prediction performance of lithium titanate oxide battery discharge capacity with machine learning methods

Enhancing the electrochemical activation kinetics of V2O3 for high-performance aqueous zinc-ion battery cathode materials

The discharge capacity and lifespan of zinc ion batteries currently remain impractical due to limitations in the cathode. Low-valence vanadium oxides are promising cathode material precursors that can be electrochemically converted into highly active hydrated amorphous oxides. However, the activation process itself suffers from structural instability or high local strain, due to the low electronic conductivity and the limited ion diffusion kinetics. To tackle this issue, herein, we synthesize porous carbon-coated nitrogen-doped V2O3 (p-NVO@C) microparticles utilizing a nitrogen-containing vanadium-based metal–organic framework (MOF) as the precursor. The uniform N doping and carbon coating improve the electronic conductivity of the active material particles. The carbon coating also traps the active material to reduce its dissolution loss; the high porosity of the p-NVO@C alleviates the stress from Zn2+-intercalation-induced expansion and shortens the ion transport paths. Moreover, first-principles calculations indicate that the doped N atoms in vanadium oxides generate a locally enhanced electric field, which accelerates the diffusion of Zn2+. Given the above advantages, the p-NVO@C particles demonstrate an outstanding specific capacity of 501 mAh/g at a current density of 0.2 A/g and a remarkable rate performance after the initial activation. The capacity retention rate remains as high as 95.7 % after 2000 cycles at a current density of 10 A/g. Ex-situ characterizations confirm the robust structural stability during phase transition cycles. This work provides an excellent solution to developing cathode materials for high-performance aqueous zinc ion batteries.

Effect of the anionic composition of sulfolane based electrolytes on the performances of lithium-sulfur batteries

In lithium-sulfur batteries, cell design, specifically electrolyte design, has a key impact on the battery performance. The effect of lithium salt anion donor number (DN) (DN[PF6]− = 2.5, DN[N(SO2CF3)2]− = 5.4, DN[ClO4]− = 8.4, DN[SO3CF3]− = 16.9, and DN[NO3]− = 21.1) on the patterns of lithium-sulfur batteries and lithium metal electrode performances with sulfolane-based electrolytes is investigated. An increase in DN of lithium salt anions leads to an increase in the depth and rate of electrochemical reduction of sulfur and long-chain lithium polysulfides and to a decrease in those for medium- and short-chain lithium polysulfides. DN of lithium salt anions has weak effect on the discharge capacity of lithium-sulfur batteries and the Coulomb efficiency during cycling, with the exception of LiSO3CF3 and LiNO3. An increase in DN of lithium salt anions leads to an increase in the cycling duration of lithium metal anodes and to a decrease in the presence of lithium polysulfides. In sulfolane solutions of LiNO3 and LiSO3CF3, lithium polysulfides do not affect the cycling duration of lithium metal anodes.

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3D Fiber Network Enhanced Composite Polymer Electrolytes for All-Solid-State Sodium Batteries

All-solid-state sodium batteries (ASSBs) coupled with solid polymer electrolytes (SPEs) are considered a promising candidate for next generation energy-storage systems due to high energy-density, low-cost, and high-safety. However, the insufficient ionic conductivity and poor interfacial stability with Na metal anode of SPEs severely hinder their commercial applications. To tackle these issues, we designed a type of inorganic/polymer composite polymer electrolytes by dispersing the unique anion-trapping 3D fiber network with abundant Lewis-acid sites in the polymer matrix to realize ultra-stable ASSBs. The rich Lewis-acid sites exposed on the 3D fiber surface can grab anions to promote the dissociation of Na salts, thus significantly improve Na+ selective migrating ability. Meanwhile, the continuous channel formed between 3D fiber network and polymer matrix provides a fast Na+ transport path, further leading to high ionic conductivity. Importantly, the Na+ transference number can also be enhanced due to the anion-trapping effect, which will effectively limit anion migration, thus regulating Na+ concentration distribution for constructing stable electrolyte/Na anode interface. Based on such advantages, the resulting composite polymer electrolyte will simultaneously exhibit high ionic conductivity, considerable Na+ transference number, as well as enhanced interfacial stability toward Na metal anode. Consequently, the electrochemical properties, including discharge capacity, cycling stability, rate capability, and safety of all-solid state sodium batteries using these 3D fiber network enhanced composite polymer electrolytes will be remarkably improved. We believe that such a composite electrolyte design could provide an effective strategy for the construction of high safe and high energy-density all-solid-state rechargeable batteries. Figure 1

Flash-pyrolyzed coal char as a high-performance anode for sodium-ion batteries

This work explores a novel approach for improving the sodium-ion battery performance of coal char using flash pyrolysis and an ether-based electrolyte. Coal char is an ultra-low cost hard carbon with promising application as an anode material in sodium-ion batteries. During flash pyrolysis, char is heated at 1000 °C/s in a drop-tube furnace to create a highly-irregular structure. The larger d-spacing and smaller closed micropore diameter of flash-pyrolyzed char increases anode capacity compared to traditional slow-pyrolyzed char electrodes. The sodium-ion battery anode performance of flash-pyrolyzed char is further improved using an ether-based electrolyte in place of the traditional ester-based electrolyte. Performance improvements include greater initial Coulombic efficiency (58% in ester- vs. 64% in ether-based electrolyte) and improved specific capacity in an ether-based electrolyte. Overall, the combination of flash pyrolysis and ether-based electrolyte increases the sodium-ion battery discharge capacity of coal char by over 50%, from 72.5 mAh g−1 (slow-pyrolyzed char in ester-based electrolyte) to 109.4 mAh g−1 (flash-pyrolyzed char in ether-based electrolyte) (50 mA g−1 discharge rate). The results highlight improvements that can be realized through flash pyrolysis of coal char for battery applications and the numerous processing advantages of flash vs. slow pyrolysis.

Experimental Study on the Thermal Management Performance of Lithium‐Ion Battery Using Phase‐Change Material at Various Ambient Temperatures

The implementation of a battery thermal management system (BTMS) is crucial to ensuring the optimal functioning of lithium‐ion batteries (LIBs) within an appropriate temperature range. In this study, BTMS with a combination of paraffin wax (PA), expanded graphite, and copper foam (CF) is investigated. The impact of various optimization strategies on battery surface temperature and discharge capacity is investigated, and charging and discharging experiments are performed at different ambient temperature conditions. Moreover, the influence of copper foam arrangement on BTMS is studied. The experimental results demonstrate that PA/CF can lead to a significant battery surface temperature reduction of up to 11.7%. Compared with the side radial arrangement, the front tangential arrangement of closely attaching copper foam to the battery leads to improved results. However, the variation in arrangement has minimal impact on the surface temperature of the battery in extreme environmental conditions. Under low‐temperature conditions, incorporating phase‐change materials could produce insulating effects that supported maintaining battery capacity. In all, this study shows the potential of designing a high‐performance BTMS and contributes to addressing heat accumulation and capacity attenuation during the use of LIBs.

Experimental and Simulation Studies on the Thermal Characteristics of Large‐Capacity Square Lithium‐Ion Batteries with Low‐Temperature Discharge

As the capacity of lithium‐ion batteries decays severely at low temperatures, it is important to study the electrochemical and thermal properties of lithium‐ion batteries at low temperatures. Herein, a large‐capacity prismatic lithium‐ion battery is selected to carry out experiments to study the electrothermal characteristics of the battery in different temperatures (25, 0, −10, and −20 °C). Second, a pseudo‐3D electrochemical–thermal coupling model is established and the validity of the model is verified. Finally, this article analyzes the influence of ambient temperature on the thermal characteristics of the battery during discharge. The results show that the battery discharge capacity gradually decreases with the decrease in the ambient temperature. At −20 °C, the discharged electricity is 66.51% of that at room temperature. At the same time, as the ambient temperature drops, the temperature rise on the surface of the battery increases during the discharge process, and at −20 °C, the temperature rise can reach 3.86 times than that at normal temperature. In addition, the change in reversible heat percentage is negatively correlated with the discharge rate and positively correlated with the battery temperature, while the effect of the discharge rate on irreversible heat is greater than that of ambient temperature.

Application of nanomaterials in new energy batteries

With the rapid development of new energy battery field, the repeated charge and discharge capacity and electric energy storage of battery are the key directions of research. Therefore, the selection standards of electrode materials and electrolyte are continuously improved, ordinary battery materials can no longer meet the needs of development. As a new type of material, nanomaterials have been widely used in many industries due to their special structure and properties. Similarly, nanomaterials also provide new possibilities for the development of new energy batteries. This paper mainly explores the different applications of nanomaterials in new energy batteries, focusing on the basic structural properties and preparation methods of nanomaterials, as well as the applications of different nanomaterials in the positive and negative materials of new energy batteries, and forecasts the future development direction of this industry. This paper is expected to provide ideas for the research of nanomaterials and new energy batteries, and promote the national research on new batteries.

An Energy Consumption Optimization Method for Intelligent Transfer Robots in a Low-temperature Environment

The functional design and performance parameters of existing intelligent transfer robots (ITRs) have met the operational requirements for most scenarios at present. However, under the operation condition of low temperatures, the battery discharge capacity of ITRs will significantly reduce, resulting in a decrease in the efficiency of ITRs. Aiming at this problem, this paper proposes an energy consumption optimization method for intelligent transfer robots in a low-temperature environment, which can make the battery discharge capacity meet the best performance by adjusting the motion parameters of ITRs. Firstly, the optimal output current is obtained by analyzing the output characteristics of the battery in a low-temperature environment, and it is measured that the energy consumption of ITRs mainly depends on the energy used in the moving process. Then, it is proved that the moving speed of the ITR has the greatest influence on the output current of the battery based on comparative experiments. Next, the LSTM prediction model and fuzzy PID control are used to regulate the moving speed of the ITR, so that the output current of the robot battery can meet the optimal output performance in a low-temperature environment. Finally, extensive comparative experiments show that the energy consumption optimization method proposed in this paper can effectively improve the discharge capacity of robot batteries in a low-temperature environment.

Predicting future capacity of lithium-ion batteries using transfer learning method

Lithium-ion (Li-ion) batteries have numerous applications, such as electric vehicles, power tools, medical devices, drones, satellites, and utility-scale storage. Remaining useful life (RUL) prediction is a challenging task due to the highly nonlinear degradation behavior and prediction of batteries dealing with unknown future data. Online RUL prediction for Li-ion batteries plays an important role in proper battery health management. To improve the prediction accuracy of RUL, we propose a novel hybrid method based on transfer learning to predict the future capacity of Li-ion batteries. The proposed method consists of integrating an ensemble empirical mode decomposition algorithm, a support vector regression model, and a bidirectional long short-term memory with attention mechanism model to predict the state of health (SOH), where SOH is the battery cycle life and discharge capacity measured in number of cycles. In addition, we also consider keen-onset effects. The performance of RUL predictions using different starting RUL prediction points is compared with experiments. The proposed method shows that the larger the cycle number of the RUL prediction starting point, the more accurate the RUL prediction results. The relative error values for the three different charging policy target batteries using the proposed method are 6.96 %, 0.6 %, and 6.25 %, respectively. The proposed method is effective for predicting the future capacity of Li-ion batteries and can be applied to predictive maintenance.

Pentafluoropyridine additive induced SEI film regulation and remarkable performance improvement of the lithium primary batteries

Lithium primary batteries with lithium metal anode are extensively applied in the portable appliances and electronic fields for the high specific energy and power, low self-discharge and wide operating temperature. However, the application of lithium metal anode causes the safety and stability issues. Herein, the pentafluoropyridine (C5F5N) was applied as an electrolyte additive in lithium primary battery, to construct a suitable surface layer on lithium anode to increase the stabilization and electrochemical performance. With C5F5N additive, the discharge capacity of the Li primary battery increases to 422.1 mAh/g at 0.01 C, compared to 62.2 mAh/g of the pristine battery. Meanwhile, the storage performance of the batteries was also greatly enhanced with the C5F5N additive. After stored for 60 days at room temperature, the Li primary battery with additive displays a specific discharge capacity of 180.7 mAh/g, much higher than the pristine battery without additive (43.6 mAh/g). The significant improvements in capacitive and storage performances are attributed to the additive induced inhibition of decomposition of solvents and lithium salts and tuning of SEI composition on lithium anode surface. The C5F5N is a promising electrolyte additive for the further development and application of high-performance Li primary batteries.

Design and experiment of a novel stepwise preheating system for battery packs coupled with non-dissipative balancing function based on supercapacitors

Lithium-ion batteries have advantages such as low self-discharge rates, high energy density, and environmental benefits. They are widely used in electric vehicles. However, their further application is limited by the inconsistency between batteries after assembly and the reduced battery performance in low-temperature environments. This article proposes a novel stepwise preheating system for battery packs that integrates a non-dissipative balancing function based on supercapacitors. The supercapacitor acts as an energy transfer and storage medium for balancing the power battery pack and heating the preheating battery pack. The preheating battery pack serves as an energy supplier for heating the power battery pack and as an energy storage unit during the balancing process of the power battery pack. This article studies the influence of low-temperature environments on the discharge capacity of power batteries and supercapacitors, explores the impact of environmental temperature on the relationship between state of charge (SOC) and open-circuit voltage (OCV), and the SOC0-OCV relationship of batteries, and clarifies the relationship between temperature and SOC0 required to meet the maximum pulse discharge test. It develops a parameter matching method for a supercapacitor and a preheating battery pack that meets the preheating requirements of power battery pack. It designs the topology structure of a balancing system based on supercapacitors with the flying capacitor method. It uses the battery terminal voltage as a balancing variable and formulates a non-dissipative balancing control strategy under static conditions. Results show that the low-temperature preheating system can warm up the preheating battery pack from −25 °C to 0 °C within 7 min, raise the temperature of the power battery pack from −25 °C to 0 °C within 27 min, and further increase the temperature of the power battery pack to 8 °C, achieving its maximum pulse discharge test in low SOC0 (33.5 %) state. During the non-dissipative balancing process, the energy transfer in the battery prioritizes charging the preheating battery pack, the average balancing current is about 8 A, and the energy utilization rate is about 80 %. This study provides a new approach for coupling the preheating technology and the power battery pack balancing technology in low-temperature environments.

Estimation of Lithium-ion Battery Discharge Capacity by Integrating Optimized Explainable-AI and Stacked LSTM Model

Accurate lithium-ion battery state of health evaluation is crucial for correctly operating and managing battery-based energy storage systems. Experimental determination is problematic in these applications since standard functioning is necessary. Machine learning techniques enable accurate and effective data-driven predictions in such situations. In the present paper, an optimized explainable artificial intelligence (Ex-AI) model is proposed to predict the discharge capacity of the battery. In the initial stage, three deep learning (DL) models, stacked long short-term memory networks (stacked LSTMs), gated recurrent unit (GRU) networks, and stacked recurrent neural networks (SRNNs) were developed based on the training of six input features. Ex-AI was applied to identify the relevant features and further optimize Ex-AI operating parameters, and the jellyfish metaheuristic optimization technique was considered. The results reveal that discharge capacity was better predicted when the jellyfish-Ex-AI model was applied. A very low RMSE of 0.04, MAE of 0.60, and MAPE of 0.03 were observed with the Stacked-LSTM model, demonstrating our proposed methodology’s utility.

A novel method of discharge capacity prediction based on simplified electrochemical model-aging mechanism for lithium-ion batteries

Obtaining the State of Health of lithium-ion batteries and mastering its degradation laws are crucial for the utilization of Electric Vehicles. However, the prediction of discharge capacity of lithium-ion batteries requires high accuracy, which is subject to the variation of cells and the uncertainty of operating conditions. In this work, a discharge capacity prognostics method for lithium-ion batteries is developed based on a simplified electrochemical coupled aging mechanism model. Firstly, the solid-phase diffusion process is analyzed by using a simplified electrochemical model, and the particle rupture stress at different C rates is obtained. Then, based on the aging mechanisms in terms of Solid Electrolyte Interphase (SEI) layer growth model and particle volume expansion model, the SEI growth rate and correlated aging kinetics parameters are optimized by using particle swarm optimization algorithm. Finally, combined with the further analysis of aging mechanisms and variation of model parameters at early, middle, and late stage of degradation, the developed discharge capacity prediction method is verified at separate stages for batteries at 1C, 2C and 3C respectively, with the average relative error of full life cycle no more than 4 %.

Investigation and Optimization of Fast Cold Start of 18650 Lithium-Ion Cell by Heating Film-Based Heating Method

In this paper, based on the multi-scale multi-domain (MSMD) battery modeling approach, the NTGK model was used to model the 18650 cylindrical lithium-ion single battery on the electrochemical sub-scale. The model was successful, as it was able to fit the experimental voltage and temperature of the battery at different temperatures. Lithium-ion battery discharge capacity and energy output can be improved during cold starting by preheating and insulation, as demonstrated by a comparison of the impacts of heat transfer coefficient and preheating duration at −20 °C ambient temperature. For the traditional heating method, the heating model of heating film (HF) and liquid-cooled plate (LCP) is constructed in this paper, and the heating performance of both is compared by Fluent. Analysis of the energy balance of Li-ion battery at low temperatures has been presented, showing that Li-ion battery requires a suitable start-up temperature to maximize energy output. Taking care of the problem of excessive temperature difference inside the battery due to excessive heating power, we investigated the effects of axial thermal conductivity, heating power, and heating area on the heating uniformity of the battery in this paper. Finally, a multi-stage stepped power (MSP) heating method was proposed to improve the temperature control accuracy of HF. A level orthogonal test L16(43) without interaction was designed to determine the degree of influence of each parameter on the temperature control performance and the optimal level combination, revealing that the optimized maximum temperature and temperature control rate were reduced by 4.09% and 40.53%, respectively, when compared to direct heating.