Battery Discharge Process Research Articles

N and Fe Doped-Carbon Aerogel for High Performance of Oxygen Reduction Reactions Electrocatalyst in Magnesium-Air Battery

The development of seawater batteries has constraints on oxygen reduction reactions in the battery discharge process that runs slowly. Therefore, an electrocatalyst is needed that accelerates the process. The electrocatalyst developed is a carbon-rich material doped with doping atoms of N and Fe. The effect of adding non-precious metal Fe to nitrogen doped carbon aerogel on the performance of the cathode electrocatalyst in seawater batteries was investigated in this study. This study began with the synthesis of cellulose pulp from palm empty fruit bunch, then progressed to the synthesis of cellulose aerogel by crosslinking NaOH‒Ammonia-Urea with the addition of Fe 5% wt., followed by pyrolysis into carbon aerogel at a temperature of 700 °C. Based on research data, N and Fe doped carbon aerogels have better seawater battery performance than N‒doped carbon aerogels without Fe. Carbon aerogels doped with N and Fe have an iron oxide phase in the form of Fe3O4 (magnetite) with a specific surface area of 2869.9 m2/g. Based on the battery test with magnesium alloy anode and 3.5% NaCl electrolyte, cathode with carbon aerogel with N-Fe codoping produces a voltage of 1.4 V, discharge energy of 269.71 mWh and discharge capacity in 1C of 189.76 mWh.

Analysis of the Effect of Battery Arrangement and Fan Parameters to the Performance of Lithium-Ion Battery Thermal Management System in Circular Configuration

This study examines the performance of a thermal management system for 18650 lithium-ion batteries using a circular placement configuration and a forward-curved fan. Experiments were conducted with variations in fan speed, the number of fan blades, and battery positioning (aligned or zigzag) to observe their effects on temperature and temperature distribution during the battery discharge process. The results showed that increasing fan speed significantly reduced battery temperature to around 30-33°C and improved temperature distribution uniformity with a standard deviation ranging from 0.5 to 1.21°C. Meanwhile, variations in the number of fan blades and battery positioning had an insignificant impact on temperature reduction but did influence temperature distribution uniformity, with the lowest standard deviation of 0.5-0.6°C observed in the three-blade variation. The zigzag positioning provided a more uniform temperature distribution compared to the aligned positioning, with a standard deviation of 0.51-0.97°C

Constructing dilute Mg-1.0In binary alloy: A pathway to enhanced anode performance in Mg-air battery

Magnesium anode is a critical material in Mg-air battery; however, the contradiction between mitigating self-corrosion and promoting activation poses a significant obstacle to the rapid advancement of primary magnesium batteries. Herein, this issue is addressed by constructing a dilute Mg-1.0In binary alloy with 1 wt% indium as the anode material. The equiaxed dendrites and moderate indium concentration gradient in the as-cast anode facilitate the formation of a protective surface film, leading to a low corrosion rate of 0.20 mm y−1 and enhancing the stability prior to discharge. Moreover, during the battery discharge process, this unique microstructure enables the redeposition of metallic indium and indium hydroxide, thereby dramatically accelerating the shedding of oxidation products and suppressing side hydrogen evolution reaction. The Mg-1.0In anode in a Mg-air battery delivers a discharge capacity of 1587 mA h g−1 and an average voltage of 1.46 V at 10 mA cm−2, outperforming most of previously reported magnesium anodes and the control samples with various indium contents. This work would inspire the achievement of superior Mg-air battery performance through the use of binary magnesium anode system in as-cast state, as opposed to a more complex and time-consuming multi-component anode design involving heat treatment and plastic deformation.

Optimal design and control strategy for enhanced battery thermal management

The Battery Thermal Management System (BTMS) plays a crucial role in the safety and performance of new energy vehicles. This study proposes an innovative cooling structure design that ingeniously combines the advantages of air cooling, water cooling, and Phase Change Materials (PCMs) to enhance the cooling efficiency of the battery system. Through numerical simulations, the effectiveness of this cooling system was validated and further supported by experimental evidence confirming the accuracy of the simulation results. Subsequently, this research utilized the Response Surface Methodology (RSM) to optimize key parameters of the cooling structure, including the fin height, gap length, and PCM thickness, with their optimal values determined to be 5.20 mm, 17.69 mm, and 3.38 mm, respectively. This parameter optimization work provides precise guidance for the design of battery thermal management systems, contributing to enhanced heat dissipation performance. To further enhance the intelligence of battery thermal management, this study introduced a novel neural network model based on Temporal Convolutional Networks (TCN) and Bidirectional Long Short-Term Memory (BiLSTM) with Multi-Head Attention (MHA). This model is capable of predicting temperature changes during the battery discharge process in real-time with high accuracy. Based on the prediction results, this research designed an efficient control strategy that, compared to a scenario without a control strategy, demonstrated a reduction in energy consumption by 20.87 %, a decrease in maximum temperature by 2.52 K, and a reduction in the maximum temperature difference by 0.05 K. These results not only prove the effectiveness of the control strategy but also provide a new direction for the optimization of battery thermal management systems.

Beyond Catalysts: Exploring Discharge Product Growth and Intrinsic Overpotential in Lithium-Oxygen Batteries.

The lithium-oxygen (Li-O2) battery, renowned for its exceptionally high theoretical energy density, is poised to revolutionize next-generation energy storage systems. However, its practical application depends on overcoming several challenges, particularly the high cathode overpotential, which significantly diminishes the battery's energy efficiency and durability. This study delves into the interactions at the cathode surface during oxygen reduction and evolution reactions (ORR/OER), extending the analysis beyond the initial reaction stages to encompass the extensive charge-discharge process. We introduce and define the concepts of intrinsic equilibrium potential and intrinsic overpotential, demonstrating that these critical parameters are predominantly influenced by the growth of discharge products, rather than the catalysts, thereby underscoring the inherent properties of the battery. This shift in focus from merely enhancing cathode catalysts to understanding and leveraging the intrinsic characteristics of the battery discharge process opens new avenues for optimizing and enhancing the performance of large-scale Li-O2 batteries. Furthermore, our findings indicate potential broader applications to other metal-oxygen systems, paving the way for the design of high-capacity, high-efficiency energy storage technologies.

Optical characterization sensing method of TFBG sensor for battery electromotive force monitoring.

In the past few years, fiber optic sensors have demonstrated an amazing ability to detect the state of charge (SOC) and electromotive force (EMF) inside a battery in real-time. However, it remains an enormous challenge to characterize the relationship between the spectral shift of the fiber sensor and the internal EMF change of the battery. Here, we propose a method to monitor the electrolyte during the battery discharge process using the integral spectrum of a tiny tilted fiber Bragg grating (TFBG) sensor. The relationship between the fiber optic transmission spectrum and battery EMF was established by using this method. The results show that a TFBG sensor implanted in a lead-acid battery enables rapid EMF detection with a sensitivity of 1.16 × 105 (nm·dBm) /V. This technology provides a fiber optic precision solution for battery operating conditions and has excellent potential for detecting battery failures using traditional EMF methods.

Identification of Flowing Electrolyte Lead Acid Battery Operating Voltage

Identification of the operating voltage of a lead acid battery with 30% sulfuric acid electrolyte flow has been carried out. The battery consists of six cells with Pb and PbO as electrodes. The battery is equipped with a 1200 ml reservoir system to collect electrolyte and supply electrolyte to each cell. Each cell has electrolyte inlets and outlets at the top and bottom that circulate through each cell using a peristaltic pump. The battery prototype built was tested for five charge-discharge cycles with a constant current of 2 A for the charging process and 0.5 A for the discharging process using Turnigy Accucell. During the charge-discharge cycle test, monitoring and recording of voltage data is carried out using a Laptop PC. Data processing uses WebplotDigitizer and Microsoft Excel for data graphing. The results are analyzed and used to identify the operating voltage of the battery by taking the average voltage over five charge-discharge cycles. The average voltage is 13.98 V for the charging process and 12.11 V for the discharging process. Six-cell battery with full capacity works at a voltage range of 12.11-13.98 V. In the process of charging with a constant current of 2 A, the battery takes an average of 7.49 hours. So, the charging capacity can be estimated at 14,980 mAh. Whereas the battery discharge process takes an average of 11 hours with a constant current of 0.5 A to a voltage drop of 10.81 V. The resulting capacity of the discharged battery is 5500 mAh.
 Keywords: flowing electrolyte, lead acid battery, operating voltage

Anisotropic Amorphization and Phase Transition in Na2 Ti3 O7 Anode Caused by Electron Beam Irradiation.

Na2 Ti3 O7 is considered one of the most promising anode materials for sodium ion batteries due to its superior safety, environmental friendliness, and low manufacturing cost. However, its structural stability and reaction mechanism still have not been fully explored. As the electron beam irradiation introduces a similar impact on the Na2 Ti3 O7 anode as the extraction of Na+ ions during the battery discharge process, the microstructure evolution of the materials is investigated by advanced electron microscopy techniques at the atomic scale. Anisotropic amorphization is successfully observed. Through the integrated differential phase contrast-scanning transmission electron microscopy technique and density functional theory calculation, a phase transition pathway involving a new phase, Na2 Ti24 O49 , is proposed with the reduction of Na atoms. Additionally, it is found that the amorphization is dominated by the surface energy and electron dose rate. These findings will deepen the understanding of structural stability and deintercalation mechanism of the Na2 Ti3 O7 anode, providing new insight into exploring the failure mechanism of electrode materials.

Steady and transient sensitivity investigations on a passive battery thermal management system coupling with phase change materials and heat pipes: Full numerical modeling and orthogonal tests

For safety reasons, the temperature distribution of the battery pack should be kept within a reasonable range. Therefore, in the present research, a passive battery thermal management system (BTMS) coupling with phase change material (PCM) and heat pipes (HP) was proposed. Full CFD (Computational Fluid Dynamics) models validated well by the experimental results were adopted for this research. Firstly, the sensitivity of parameters such as PCM type, PCM thickness and ambient temperature on the thermal performance of BTMS was obtained by orthogonal tests. Numerical results show that the greatest influence on the maximum temperature is the ambient temperature. In the variance analysis showed that the PCM thickness has a significant effect on decay the battery temperature difference. Furthermore, operational range and variance analysis confirmed the optimal BTMS, i.e., with PCM3 thickness of 3 mm and ambient temperature of 30 °C. Subsequently, transient modeling and analysis of the battery discharge process were carried out. Unsteady results showed that the maximum temperature of the battery was reduced from 68.90 °C to 43.19 °C, and simultaneously, the maximum temperature difference dropped from 16.58 °C to 3.66 °C. In the process of battery discharge, PCM was properly adjusted regarding of its thickness; whereas, its melting temperature should be kept approaching to the ambient temperature, which was beneficial to the operational safety of the battery. In addition, temperature distribution of the battery has a linear relationship to the ambient temperature; when every 5 °C increase was observed in ambient temperature, the maximum temperature of the battery was boosted by 2.3 °C and the temperature difference was reduced by 1.2 °C, separately. Present research, straightforwardly maintaining the temperature distribution of the power battery in a safe and efficient range, could be significant for improving energy utilization and reducing extra energy consumption of the power battery, simultaneously.

EVALUATION OF THE EFFECT OF EXTERNAL ENVIRONMENT TEMPERATURE VARIATION ON THE DISCHARGE OF UAV BATTERY

This article addresses the crucial aspect of optimizing continuous perimeter monitoring systems for protecting critical infrastructure facilities. The study focuses on the energy consumption of multirotor Unmanned Aerial Vehicles (UAVs) under varying ambient temperature conditions. As these facilities require constant protection, integrating various technical means, including UAVs, into a unified security framework enhances effectiveness.
 The paper introduces a novel method for assessing the influence of ambient temperature on the energy consumption of multirotor UAVs during flight. Experimental data are utilized to calculate the battery efficiency coefficient, accounting for temperature variations and atmospheric pressure. This coefficient serves as a valuable parameter for estimating the duration of UAV flights, especially during prolonged monitoring missions.
 The conclusions drawn from the study emphasize the significant role of ambient temperature in the battery discharge process during extended flights. Implementing the calculated efficiency coefficient in the planning phase can optimize the UAV’s operational lifespan and enable precise predictions of flight durations in various weather conditions.
 This research holds great practical significance as it contributes to the efficient utilization of UAVs in continuous perimeter monitoring systems. The findings provide valuable insights into energy consumption patterns, allowing security personnel to plan UAV deployment and optimize surveillance operations effectively. Ultimately, this knowledge enhances the overall security of critical infrastructure facilities, safeguarding them from potential threats and unauthorized access.

Meso-scale simulation of Li–O2 battery discharge process by an improved lattice Boltzmann method

The discharge process of lithium–oxygen battery (LOB) is a highly complicated multi-physics coupling phenomenon. Moreover, the cathode morphology presents a complex multi-scale structure with pore size ranging from nanometers to micronmeters, and plays a crucial role in determining the discharge performance. In this work, the cathodes consisting of carbon paper, electrode material, and electrolyte are first numerically reconstructed using a two-step reconstruction method considering the multi-scale morphology. A lattice Boltzmann model with an improved partial bounce-back scheme is proposed for modeling the discharge process given that the electrode porosity changes with the progress of discharge. The effects of micron-scale electrode spatial distribution on the O2 diffusion and LOB discharge performance are investigated. Results show that the increment of the electrode dispersion degree increases the O2 diffusion resistance due to the increase of electrolyte-electrode specific interface area. A large local electrode load near O2 inlet leads to a high O2 diffusion resistance and low O2 concentration owing to the large specific interface area and electrode volume. Cathodes with the minimum electrode load and maximum electrode dispersion degree present the optimal specific capacity of LOB. However, the specific capacity first increases significantly and then slightly decreases with the increase of local electrode load.

Endurance estimation in hovering flight based on battery power requested on quadcopter UAV

In this era, Unmanned Air Vehicle (UAV) application is growing. However, there are still weaknesses in using UAVs to carry out certain missions. One of the major problems is the energy and power required to use the UAV which impacts the endurance of a UAV can hover. This study focuses on calculating the endurance and finding which configuration will produce the optimal endurance. It starts by calculating the thrust of a propeller using blade element theory which ends in calculating endurance. Using four different types of propellers, an integral formulation was devised for a constant–power battery discharge process to predict the hovering time. The result shows that APC 1238 combined with battery 6S will produce the longest endurance. The methodology is applicable for a custom quadcopter UAV.

Performance analysis and optimal sizing of electric multirotors

This paper presents an analytical framework for addressing the hovering performance of a battery–powered multirotor. The estimation of power required for flight is investigated and an analytical model is proposed to describe the rotor figure of merit as a function of few relevant blade parameters, without the need for ad hoc experiments. The model is derived after a discussion about the aerodynamics of rotating blades. The formulation in terms of Reynolds number is supported by an experimental campaign, performed on a set of commercial–of–the–shelf propellers optimized for small–scale multirotor applications.By imposing the balance between required and available power, the hovering time is predicted by an integral formulation developed for a constant–power battery discharge process. The best endurance condition is obtained in terms of optimum battery capacity and flight time. The methodology, applicable to the design phase of novel multirotor configurations, is finally validated by flight tests.

Modeling electrochemical properties of LiMn_{1-x}Co_{x}BO_3 for cathode materials in lithium-ion rechargeable batteries

In this work, we report first-principle calculations of the electrochemical properties of lithitated and delithiated LiMn_{1-x}Co_{x}BO_3 (x = 0, 0.25, 0.5, 0.75, 1) crystals based on the density functional theory (DFT) with the generalized gradient approximation (GGA) and also considering the on-site Coulomb interaction, the so-called Hubbard correction. We found that the top of the valence band and the bottom of the conduction band of these crystals are mainly formed by the hybridization of the 3d orbitals of mixed Mn_{1-x}Co_{x} ions and oxygen 2p orbitals. We observed a band gap narrowing with an increase of cobalt concentration and that the Hubbard correction implies a better theoretical description of their electronic structures. When considering the delithiated materials, our calculations show a metallic behavior for intermediate cobalt concentrations (x = 0.25, 0.5, 0.75), which is a good quality for cathodic materials, as it improves the battery discharge process. We also obtained high (4.14 V vs. Li^+/Li^0 and 4.16 V vs. Li^+/Li^0) open circuit voltage (OCV) values at cobalt concentrations of x = 0.5 and 0.75, where we believe that if these high OCV values are accompanied by a high charge storage capacity, these compounds can become promising and useful cathode materials. Finally, our results are in accordance with previous calculations and also with experimental results.

Desain Sistem Pendingin Kemasan Baterai Litium Ion Kapasitas Pengisian Cepat dengan PCM (Phase Change Material) dan Pelat Pendingin

Battery performance is affected by the problem of overheating which can cause mechanical damage to the battery and electronic components of the BMS (Battery Management System). With the need for an increase in battery charging time with fast capacity, the internal heat generated by the battery also increases so that the battery pack needs to be equipped with a cooling system. Currently, the cooling system in the battery pack uses a lot of cooling plate, cooling pipe, PCM (Phase Change Material) and cooling fluid. Combining cooling system design based on advantages and disadvantages to produce the best performance was tried using the cooling plate and PCM. The method used is to change the initial design of the battery pack without cooling to a cooling system by making a design and verifying the design. The process of thermal analysis is carried out in the process of charging the battery and removing the battery. The result of the research is the distribution of heat transfer that occurs during the battery charging process and the battery discharge is uniform and the temperature value obtained is the 43,2 °C battery discharge process in the main cooling plate component and the maximum temperature in the charging process is 57,6°C. at BMS. Cooling using a cooling plate and PCM for a closed system is maximized. Keywords: baterai Litium-Ion, Heat Sink, PCM

Estimate method research at working life of wireless sensor network nodes

Process deep research at disposable lithium sulfite chloride battery discharge characteristics and current-voltage characteristics when wireless sensor panel point working. Test the voltage-current time domain signal during the disposable lithium sulfite chloride battery discharge process and wireless sensor panel point working process through high precision power consume test instrument. Research and design one calculate method of wireless sensor panel point power consume. Build the estimate model for wireless sensor used battery power. Develop the wireless sensor network battery working life estimate and early warning method which based on the power consume calculate method of wireless sensor and wireless sensor used battery power estimate model, make users able to real time and accurately grasp all wireless sensor network panel point’s working life through this method, at the same time, can real time monitored whether battery of wireless sensor network panel points or the relate electric circuit of power supply exist problems, do well at wireless sensor panel point running and maintain works in advance. Finally, use high precision instrument process test and verify pulse voltage characteristics at wireless sensor panel point actual work which supply power by disposable lithium sulfite chloride battery, the test results are unanimous with theory research.

Fast conversion and controlled deposition of lithium (poly)sulfides in lithium-sulfur batteries using high-loading cobalt single atoms

Lithium-sulfur (Li–S) batteries are appealing energy storage technologies owing to their exceptional energy density. Their practical applications, however, are largely compromised by poor cycling stability and rate capability because of detrimental shuttling of polysulfide intermediates, complicated multiphase sulfur redox reactions, and uncontrolled precipitation of the discharge products (lithium sulfide, Li2S). Herein, monodispersed Co single-atom catalyst on conductive nitrogen-doped carbon nanosheet (CoSA-N-C) with high Co content of 15.3 ​wt% was fabricated through a salt-template method and used as a sulfur host material to simultaneously alleviate the polysulfide shuttling, propel the redox kinetics of dissolved polysulfides, and mediate the deposition of Li2S. The robust two-dimensional architecture of CoSA-N-C with large surface area, high porosity, and dual lithiophilic-sulfiphilic Co–N species enable strong physical and chemical polysulfides confinement and fast electrons/ions transfer process. The densely populated Co–N4 coordinated moieties function as electrocatalytic sites to accelerate the reversible conversion between lithium polysulfides and Li2S. Importantly, the CoSA-N-C enables spatially controlled deposition of Li2S nanoparticles during the battery discharge process, as opposed to conventional Li2S passivation layers that fully covered the conductive host. Consequently, the as-fabricated cathodes based on the CoSA-N-C deliver high sulfur utilization (1574 mAh·g−1 at 0.05 ​C), outstanding rate capability (624 mAh g−1 at 5 ​C) and superior long-term stability (capacity fade rate of 0.035% per cycle for 1000 cycles at 1 ​C). Even under a sulfur loading up to 4.9 ​mg ​cm−2, the reversible areal capacity could reach 4.24 mAh cm−2 after 120 cycles at 0.2 ​C, delivering an ultrahigh capacity retention of 91.8%. This work sheds inspiring insights on the important role of single atomic metal with high mass loading in mediating the deposition of lithium sulfides and accelerating the reversible conversion of lithium polysulfides toward decent-performance Li–S batteries.

Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising

Batteries are often packed together to meet voltage and capability needs. However, due to variations in raw materials, different ages of equipment, and manual operation, there is inconsistency between batteries, which leads to reduced available capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack similar batteries together. The conventional approach to screening batteries is based on their capacity, voltage and internal resistance, which disregards how batteries perform during manufacturing. In the battery discharge process, real time discharge voltage curves (DVCs) are collected as a set of unlabeled time series, which reflect how the battery voltage changes. However, few studies have focused on DVC based battery screening. In this paper, we provide an effective approach for battery screening. First, we apply interpolation on DVCs and give a method to transform them into slope sequences. Then, we use density-based spatial clustering of applications with noise (DBSCAN) for denoising and treat the remaining data as input to the K-means algorithm for screening. Finally, we provide the experimental results and give our evaluation. It is proved that our method is effective.

Mathematical Model of Lithium-Ion Battery Cell and Battery (Lib) on its Basis

The article considers a mathematical model of lithium-ion battery cell and battery (LIB) on its basis. The developed mathematical model allows predicting LIB temperature on different parts of its surface during charging and discharging by nominal and maximum currents. The results of the battery discharge process simulation and validation of the mathematical model based on the field experiment results are also presented

Wczesne przewidywanie czasu pozostałego do rozładowania baterii litowo-jonowej z uwzględnieniem korelacji parametrów z różnych etapów procesu rozładowania

In this paper, we propose a method for making early predictions of remaining discharge time (RDT) that considers information about future battery discharge process. Instead of analyzing the entire degradation process of a battery, as in the existing literature, we obtain the information about future battery condition by decomposing the discharge model into three stages, according to level of voltage loss. Correlation between model parameters at the first and last stages of discharge process allows the values of model parameters in the future to be used to predict the value of parameters at early stages of discharge. The particle swarm optimization (PSO) and particle filter (PF) algorithms are employed to update parameters when new voltage data is available. A case study demonstrates that the proposed approach predicts RDT more accurately than the benchmark PF-based prediction method, regardless of the degradation period of the battery.