Discharge Rate Research Articles

The capacity degradation path prediction for the prismatic lithium-ion batteries based on the multi-features extraction with SGPR

Accurate capacity degradation path estimation of lithium-ion batteries plays a crucial role in ensuring the safety and reliability of electric vehicles. In recent years, the evolution of the status of health (SOH) prediction with machine learning techniques has become a research hotspot because of its powerful computing power and robustness. Thus, this study employes the sparse gaussian process regression (SGPR) data-driven approach with multi-features extracted from the battery cycling processes to project the potential degradation patterns of the lithium-ion batteries. Firstly, a battery life test platform was built. The accelerated life aging tests of batteries at different temperatures (25 °C, or 60 °C) and different discharge rates (1C, or 2C) were conducted to establish the dataset for the multi-features extraction and training of the SGPR algorithm. Secondly, different battery characteristic features were extracted based on the battery cycle charge-discharge curves. Various order-reduction treatments, i.e., the filter-based, embedding-based, and fusion-based selection algorithms, were performed to suppress the over-fitting and improve the estimate's accuracy. Finally, using the extracted features as inputs, SGPR models are constructed to estimate the degradation path of the battery. With the 50 % training data, the SGPR has a higher estimation accuracy than the regular GPR, and the average maximum absolute errors for the batteries are 2.80 %, 1.22 %, 3.57 %, and 1.83 %, respectively.

Impact of the geriatric emergency medicine specialist intervention on final emergency department disposition.

The Geriatric Emergency Medicine Specialist (GEMS) pilot program is an innovative approach that utilizes geriatric-trained advanced practice providers to facilitate geriatric assessments and care planning for older adults in the emergency department (ED). The objective of this study was to explore the effect of GEMS on the use of observation status and final ED disposition. This was a retrospective study under a target trial emulation framework. Geriatric patients (65+ years old) who presented to two ED sites within a large regional healthcare system between December 2020 and December 2022 were included. The primary outcome was final ED disposition (discharge, hospital inpatient admission, or hospital observation admission). Secondary outcomes included ED observation and ED length of stay. Non-GEMS patients were propensity score matched 5:1 to GEMS patients. Doubly robust regression was used to estimate the odds ratios and 95% confidence intervals of inpatient admission, discharge, hospital observation admission, ED observation admission, and estimate the mean ED length of stay. A total of 427 of 43,064 total patients (1.0%) received a GEMS intervention during the study period. Our analysis included 2,302 geriatric ED patients (410 GEMS, 1,892 non-GEMS) after propensity score matching. Hospital admission rates were 34.1% for GEMS compared to 56.4% for conventional treatment. GEMS patients had decreased odds of inpatient admission (OR: 0.41, 95 CI: 0.34-0.51, p < 0.001), increased odds of discharge (OR: 1.19 95 CI: 1.00-1.42, p = 0.047), hospital observation admission (OR: 2.97, 95 CI: 2.35-3.75, p < 0.001), ED observation admission (OR: 4.84 95 CI: 3.67-6.38, p < 0.001), and had a longer average ED length of stay (170 min, 95 CI: 84.6-256, p < 0.001) compared to non-GEMS patients. Patients seen by GEMS during their ED visit were associated with higher rates of hospital discharge and lower rates of hospital admissions.

Effects of salinity stress on physiological behavior, respiratory metabolism, and intestinal transcriptome of juvenile Stichopus monotuberculatus

This study investigated the impacts of salinity stress on the physiological behavior, respiratory metabolism, and transcriptome of artificially cultured juvenile Stichopus monotuberculatus (S. monotuberculatus) (with a body weight of 3.23 ± 0.60 g). S. monotuberculatus individuals cultured in artificial seawater were transferred to artificial seawater with salinities of 20‰, 30‰, and 40‰ for salinity stress treatment. The physiological behavior of S. monotuberculatus was observed, and their ammonia discharge rates, oxygen consumption rates, and oxygen/nitrogen (O/N) ratios were measured. After 24 h of stress, the intestines of S. monotuberculatus were collected for transcriptome sequencing. The results showed that both hyper-salinity and hypo-salinity stresses significantly affected the physiological status of S. monotuberculatus. The oxygen consumption and ammonia discharge rates of the hyper-salinity group (40‰) and hypo-salinity (20‰) group were remarkably higher than those of the control group (P<0.05), and the O/N ratios of the two groups were significantly lower than those of the control group (P<0.05). Sequencing identified a total of 3840 differentially expressed genes (DEGs) from the salinity-stress groups and the control group. GO analysis revealed that DEGs were mainly enriched in biological processes, cellular components, and molecular functional categories, with the highest enrichment observed in cellular processes, metabolic processes, membranes, binding, and catalytic activities. KEGG analysis showed that the DEGs of hyper-salinity and hypo-salinity groups were enriched in different secondary pathways, with the expressions of related genes significantly upregulated, indicating that S. monotuberculatus may adapt to hyper-salinity and hypo-salinity environments through various regulatory mechanisms. The results verify that salinity stress significantly affects the physiological behavior and respiratory metabolism of S. monotuberculatus. S. monotuberculatus respond to hyper-salinity and hypo-salinity stresses by increasing protein consumption and adopting different adaptation mechanisms. Furthermore, S. monotuberculatus exhibits stronger tolerance to hypo-salinity environments compared to hyper-salinity ones.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity.

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

E013 Looking back at back pain: how well do our referrals measure up to available criteria?

Abstract Background/Aims According to the Global Burden of Disease Study 2021, low back pain remains the leading cause of years lived with disability (YLDs) globally affecting about 619 million people as of 2020. Inflammatory back pain affects fewer patients but remains an important referral indication. A previous audit from the early back pain clinic of cases seen between 2015-16 at the Royal National Hospital for Rheumatic Diseases, Bath, identified an axial spondyloarthritis (AxSpA) diagnosis in 21% of patients of whom, two thirds were HLAB27 positive. This follow-up audit aimed to evaluate for interval change in axSpA prevalence and assess the referrals against NICE and ASAS criteria respectively. While the NICE referral guidance is largely clinical, ASAS incorporates extra musculoskeletal manifestations and investigations. Methods We reviewed 100 of the 271 early back pain clinic referrals received between July 2022-23. The completed referral proforma was evaluated against the NICE and ASAS criteria respectively. Electronic medical records and clinic letters of patients were also reviewed including demographics, baseline investigations and imaging. Results The patients were 54% male with an average age of 38.7 ± 13.7years. An axSpA diagnosis was made in 19 patients (19%) of which 12 were HLAB27 positive (63.1%). The median symptom duration was 24 months (6-72) with an appointment delay of 128 days (36-182). Discharge rate was 35% after the first appointment. Overall, 62% of referrals satisfied NICE criteria compared to 71% for ASAS. This was after excluding 21 referrals which did not satisfy the ASAS entry criterion of symptoms &amp;gt; 3months in patients &amp;lt;45 years. Among our cohort, sensitivities were 68.4% for NICE and 73.7% for ASAS while specificities were 39.5% for NICE and 29.6% for ASAS. Three patients all above 45 years with a normal CRP met neither criteria, but were diagnosed with axSpA after MRI while one patient who satisfied both criteria turned out to have lung cancer with bony metastases. Conclusion There has been minimal interval change in AxSpA prevalence from our referrals between 2015-23. The ASAS criteria was easier to satisfy and can serve as an alternative referral indication for patients who do not meet NICE criteria. Both criteria are still very useful in terms of ensuring the quality of referrals received. Improvements in the referral pathway are being planned to reduce primary and secondary care delays thus enhancing earlier diagnosis and treatment. Disclosure A. Akpabio: None. M. Camillieri: None. T. Williams: None. R. Sengupta: None.

Improving the Performance of LiNi0.9Co0.05Mn0.05O2 via Atomic Layer Deposition of ZnxOy Coating

AbstractNickel‐rich cathode materials such as LiNi0.9Co0.05Mn0.05O2 (NMC90) have gained attention due to their ability to deliver high energy densities while being cost‐effective for Lithium‐ion battery manufacturing. However, NMC90 cathodes suffer irreversible parasitic reactions such as electrolyte decomposition, severe capacity fading and impedance build‐up upon prolonged cycling. Herein, we synthesize a conformal ultrathin, surface protection layer on NMC90 powder using ZnxOy via atomic layer deposition technique (ZnxOy@NMC90). Prolonged electrochemical investigation of full cells at high discharge rates of 2 C shows that ZnxOy@NMC90 cells yielded ~31 % improvement in discharge capacity compared to pristine NMC90. Furthermore, operando electrochemical mass spectroscopy studies show that the ZnxOy@NMC90 cells have significantly suppressed electrolyte decomposition as compared to pristine NMC90 cells. Post‐cycling electrochemical impedance spectroscopy studies show that the ZnxOy@NMC90 full cells have significantly reduced impedance compared with pristine NMC90 cells. Additionally, post cycling manganese dissolution studies show that ZnxOy@NMC90 cells have greatly enhanced chemo‐mechanical integrity thereby contributing to improved electrochemical performances. Our results underscore the potential of tailored ZnxOy surface coatings on nickel‐rich cathode materials to address critical challenges in advanced energy storage systems, offering promising prospects for the development of high‐energy‐density lithium‐ion batteries.

An Electrochemical-Thermal Coupling Model Based on Two-Factor Parameter Modification for Lithium-Ion Battery

Abstract The accurate establishment of battery model can improve the design reliability and reduce the design risk, which provides an important basis for the research of battery. First, the key parameters of the Li-ion battery model are identified by the least square method based on the full-battery equivalent circuit model of the single-particle impedance spectrum, and the diffusion coefficient and exchange current density under different temperatures and SOC conditions are calculated. At the same time, the one-dimensional thermal rate model is used as the heat source of the three-dimensional model, and the mean temperature T of the three-dimensional model is calculated by using Fourier's law, and T is fed back to the one-dimensional model as the key parameter to modify the conductivity, diffusion coefficient, and exchange current density, and a semi-empirical electrochemical-thermal coupling model with two-factor parameter modification is established. Finally, the model is verified by the temperature field distribution and discharge voltage curve at different discharge rates. The maximum temperature difference is less than 3.1 °C, and the maximum voltage difference error is less than 0.131 V. The results show that the improved model can accurately reflect the influence of temperature on the model parameters, and has high accuracy in the estimation of battery terminal voltage and SOC.

Experimental investigation on flame characteristics in a linear array of dual spill fire

In the process of petroleum production and transportation, a porous leakage accident can easily lead to combustion behaviors such as fire merging, resulting in more severe consequences. This study explores the combustion characteristics of merging spill fires through experimental investigations, incorporating dual leakage holes with varying spacing to examine their impact on the combustion process. The experimental results suggest that the flame height undergoes a pattern of initial decrease followed by an increase with the gradual expansion of leakage spacing, owing to the coupling effects of air entrainment and thermal radiation feedback within the additional entrainment zone. Based on the developmental pattern of flames with respect to leakage spacing, this study categorizes the dual spill fire into three states: which are: (1) full merging state, (2) intermittent merging state, and (3) separation state. The flame height prediction model is established for different merging states, considering parameters such as the fuel discharge rate and the leakage spacing of dual spill fire. The experiment reveals that the flame pulsation frequency (FPF) of the spill fire follows the pattern observed in pool fire FPF, and an FPF model for dual spill fire in all states is obtained through the fitting. Finally, the coupled heat transfer between dual fire sources is considered, and a burning rate model for dual spill fire in intermittent merging states is established.

Synthesis and characterization of coprecipitated layered NCM oxide as cathode for sodium-ion batteries: Kinetics and hydrodynamics studies

Interest in the development of high-performance sodium-ion batteries (SIBs) as a sustainable alternative to lithium-ion batteries (LIBs) for emerging energy storage systems has motivated to delve into a novel approach for the synthesis of layered transition metal oxide (LTMO) type cathode for SIBs batteries. In this study, we introduce novel chemical synthesis method that diverges from traditional methodologies reported till date. Rather than relying on sulfur, nitrate, or acetate metal precursor salts, we employ metal carbonate salt coupled with oxalic acid as a chelating agent, and sodium carbonate as a precipitating agent. This novel chemistry enhances the microstructure of the cathode material inherited from its precursor exhibiting spherical morphology, influence on the electrochemical properties, bestowing the material with high specific capacity, extended cycle life, and an elevated charge–discharge rate. The primary focus of this work centers on a comprehensive investigation of the hydrodynamic and kinetics aspects of the co-precipitation reaction, guided by the principles of chemical engineering. The effects of key parameters such as impeller speed, impeller type, and scale-up effects on the co-precipitation process have been systematically explored. This research introduces insights into optimizing reaction conditions such as pH, reaction temperature, metal precursor salt ratio, precipitating agent, through rigorous experimentation and characterization reports. The notable effect of precipitating agent on morphology has been demonstrated by electron microscopy images. The kinetics study shows the activation energy of 8.9 kJ mol−1 depicts the reaction is controlled by mass transfer resistance and to overcome this effect, impeller type and speed plays significant role and experimentation results shows the axial mixing pattern created by pitched blade impeller is effective to improvise electrochemical properties. The synthesized cathode material exhibits remarkable electrochemical properties, including tap density of approximately 1.3 g cc−1 with reversible capacity of 215 mAh g−1, along with excellent cyclic stability (90 %) over 60 cycles. Furthermore, it shows the high energy density up to 1300 Wh/L and a rapid charge–discharge rate. These findings contribute to the advancement of SIBs technology and offer promising prospects for future researchers to efficient development of high-performance energy storage solutions.

Optimizing urban green infrastructure using a highly detailed surface modeling approach

Urban trees and forests show a better ecosystem with many benefits, including pure air quality. The development of urban green infrastructure (UGI) creates a better management system that greatly impacts social values in an urban system. The UGI and construction activities are receiving much attention for their effectiveness in addressing various urban ecological, social and economic issues. Using green infrastructure in stormwater management can reduce the influence on urban sewerage systems and, eventually, on building water resources. The main goal of the research is to optimize the green infrastructure to provide a less-pollution, well-organized, and pleasurable environment for the inhabitants. Various models are used to study the present rainfall-runoff scenario, but the stormwater management model (SWMM) is the most preferable and suggested model. Once the parameters are accessed, optimizing the green infrastructure (GI) will be easy. A complete SWMM model is evaluated over the complete surface, and a hydrological measurement is presented. The evaluation study presents various component percentages: asphalt (37%), green (27%), ceiling (21%), grit (12%), and cemented area (2%), which provides rainproof coverage of approximately 60%. A design is developed about the diverse events of GI in urban exploiting the SWMM and demonstrates its stimulus on the rainfall-runoff behaviour. In recent years, very little attention has been given to green spaces in urban areas, which not only increases pollution but also decreases the urbanization. Therefore, urban green spaces are more important to improve air quality and resident living standards. Over the given scenario and the rainfall event, a decline of the quantitative discharge parameters is evident, such as discharge volume (i.e., from 3.6 to 61.8) and the peak discharge rate (i.e., from 5.4 to 62.7%). The simulation results show that green areas give high satisfaction with low construction costs, which shows the superlative performance ratio of the examined measures. From the investigation, it is also recommended to have green areas and public spaces in impervious urban areas, which greatly reduced the runoff in the project area.

Flight analysis and optimization design of vectored thrust eVTOL based on cooperative flight/propulsion control

The rise of electric vertical take-off and landing (eVTOL) aircraft has sparked research interest, but attention to modeling and evaluation methods, particularly for vectored thrust eVTOL, lags behind. The intricate flight/propulsion coupling and structure/control complexity contribute to the gap. Moreover, integrated modeling and evaluation processes for vectored thrust eVTOL should fully account for the tilting characteristics of the fan/propeller. This paper proposes a flight/propulsion cooperative control modeling and evaluation method for vectored thrust eVTOL. The methodology uses the Gaussian pseudospectral trajectory optimization method to obtain the overall characteristics and cooperative control strategy of flight/propulsion under strict take-off and landing trajectory constraints. Besides, this paper yielded the parameterized analysis and matching optimization design of the propulsion system. Results indicated that for an aircraft with a take-off weight of 1.8 tons, equipped with four 1.6 m diameter tilting ducted fans and a single discharge rate 5C battery, its cruising range is 135.1 km based on the selected technical parameters. The power consumption accounts for merely 12.6% of the total battery capacity during the take-off phase with high-power demand but short duration. By employing a pack of high-power-density and high-energy-density batteries to drive the ducted fans jointly, the aircraft's cruising range, fan size, and payload can be optimized. The 20C+2C battery scheme can either increase the cruising range by 27.3% without changing the fan diameter or increase the cruising range by 6.1% when the fan diameter is reduced to 1.1 m. Wherein without changing the fan diameter, the battery mass can be reduced from 720 kg to 571 kg while satisfying the takeoff and cruising requirements. The results demonstrated the effectiveness of improving the cruising range and optimizing the fan size and payload.

Inpatient opioid withdrawal: a qualitative study of the patient perspective.

Opioid withdrawal is common among hospitalized patients. Those with substance use disorders exhibit higher rates of patient-directed discharge. The literature lacks information regarding the patient perspective on opioid withdrawal in the hospital setting. In this study, we aimed to capture the patient-reported experience of opioid withdrawal during hospitalization and its impact on the desire to continue treatment for opioid use disorder after discharge. We performed a single-center qualitative study involving semi-structured interviews of hospitalized patients with opioid use disorder (OUD) experiencing opioid withdrawal. Investigators conducted in-person interviews utilizing a combination of open-ended and dichotomous questions. Interview transcripts were then analyzed with open coding for emergent themes. Nineteen interviews were performed. All participants were linked to either buprenorphine (79%) or methadone (21%) at discharge. Eight of nineteen patients (42%)reported a patient-directed discharge during prior hospitalizations.Themes identified from the interviews included: (1) opioid withdrawal was well-managed in the hospital; (2) patients appreciated receiving medication for opioid use disorder (MOUD) for withdrawal symptoms; (3) patients valued and felt cared for by healthcare providers; and (4) most patients had plans to follow-up for opioid use disorder treatment after hospitalization. In this population with historically high rates of patient-directed discharge, patients reported having a positive experience with opioid withdrawal management during hospitalization. Amongst our hospitalized patients, we observed several different individualized MOUD induction strategies. All participants were offered MOUD at discharge and most planned to follow-up for further treatment.

The role of colchicine in the management of COVID-19: a Meta-analysis

BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic has robustly affected the global healthcare and economic systems and it was caused by coronavirus-2 (SARS-CoV-2). The clinical presentation of the disease ranges from a flu-like illness to severe pneumonia and death. Till September 2022, the cumulative number of cases exceeded 600 million worldwide and deaths were more than 6 million. Colchicine is an alkaloid drug that is used in many autoinflammatory conditions e.g., gout, familial Mediterranean fever, and Behçet’s syndrome. Colchicine inhibits the production of superoxide and the release of interleukins that stimulate the inflammatory cascade. Colchicine decreases the differentiation of myofibroblast and the release of fibrotic mediators including transforming growth factor (TGF-β1) that are related to the fibrosis. Moreover, colchicine has been used to traet viral myocarditis caused by CMV or EBV, interstitial pneumonia, and pericarditis resulting from influenza B infection. Additionally, colchicine is considered safe and affordable with wide availability.ObjectiveThe aim of the current study was to assess the evidence of colchicine effectiveness in COVID-19 treatment.MethodsA comprehensive review of the literature was done till May 2022 and yielded 814 articles after ranking the articles according to authors and year of publication. Only 8 clinical trials and cohort studies fulfilling the inclusion criteria were included for further steps of data collection, analysis, and reporting.ResultsThis meta-analysis involved 16,488 patients; 8146 patients in the treatment group and 8342 patients in the control group. The results showed that colchicine resulted in a significant reduction in the mortality rate among patients received colchicine in comparison with placebo or standard care (RR 0.35, 95%CI: 0.15–0.79). Colchicine resulted in a significant decrease in the need for O2 therapy in patients with COVID-19 (RR 0.07, 95%CI 0.02–0.27, P = 0.000024). However, colchicine had no significant effect on the following outcomes among COVID-19 patients: the need for hospitalization, ICU admission, artificial ventilation, and hospital discharge rate. Among the PCR confirmed COVID-19 patients, colchicine decreased the hospitalization rate (RR 0.75, 95%CI 0.57–0.99, P = 0.042). However, colchicine had no effect on mortality and the need for mechanical ventilation among this subgroup.ConclusionColchicine caused a significant clinical improvement among COVID-19 patients as compared with the standard care or placebo, in terms of the need for O2, and mortality. This beneficial effect could play a role in the management of COVID-19 especially severe cases to decrease need for oxygen and to decrease mortality among these patients.

Experimental study on flexible flame retardant phase change materials for reducing thermal runaway propagation of batteries

The current research on phase change materials (PCM) for Battery Thermal Management Systems (BTMS) often focuses on a single characteristic, either flame retardancy or flexibility. PCM with both flexibility and flame retardancy is relatively uncommon, and studies on flexible PCMs have lacked experimental validation of their effectiveness. This study explored the optimal ratio of aluminium hydroxide (ATH)/ magnesium hydroxide (MTH)/ ammonium polyphosphate (APP), successfully creating a flexible flame-retardant PCM and applying it to battery cooling. The ratio of ATH/MTH/APP was determined as 9: 3:8, providing features such as leak resistance, high thermal conductivity, flame retardancy, and flexibility. Compared to the blank sample without flame retardants, the Peak Heat Release Rate (PHRR) and Total smoke production (TSP) of the PCM decreased by 48 % and 24.3 %, respectively. When applied to BTMS, the PCM restricted the battery's surface peak temperature and maximum temperature difference to 48.76 °C and 4.07 °C, respectively, at a discharge rate of 6C. After applying pressure to leverage flexibility, the temperature difference was further reduced to 1.76 °C, demonstrating the effectiveness of flexibility. In Thermal Runaway (TR) experiments, the PCM delayed the time triggered by TR by 84 s and reduced the maximum temperature by 92.3 °C. This work successfully combines flame retardancy and flexibility, offering valuable insights for the application of flame retardant flexible CPCM in BTMS and other relevant fields.

Optimizing Discharge Rate for Li Metal Stability in Rechargeable Li|NMC Batteries under Lean Electrolyte Condition

Optimizing Discharge Rate for Li Metal Stability in Rechargeable Li|NMC Batteries under Lean Electrolyte Condition

On the performance of carbon fiber structural batteries with temperature

Carbon fiber structural batteries, which combine structural and functional properties, have good energy storage capacity while bearing loads have received attention from scholars at home and abroad in recent years as a new type of energy storage device. However, in the process of use, temperature changes will lead to the occurrence of thermal stresses, which may cause structural failure under multiple cycles. In this paper, the thermal-stress coupled model of structural batteries was established first using the temperature and thermal stress models of structural batteries, considering the heat exchange with the external environment of structural batteries. Then based on the coupled model, the thermal stress in the structural battery was simulated and analyzed in COMSOL considering different charge and discharge rates and ambient temperatures of the structural batteries. The results show that: (1) The higher the charging and discharging rates, the higher the temperature of the structural battery, resulting in greater thermal stress. (2) The higher the ambient temperature of the structural battery, the longer its discharge time and the lower the voltage at which discharge terminates, which is beneficial for the electrochemical performance of the battery. But the higher the ambient temperature, the greater the temperature change inside the structural battery, which is not conducive to the mechanical performance of the structural battery. This study can provide reference for the safety analysis of structural batteries in thermal environments.

Constructing the charge channel with CFx using a well-dispersed carbon nanotube arrays to boost high-rate primary battery

Pursuing ultra-high specific energy density for lithium fluorinated carbon (Li/CFx) battery requires a high fluorine to carbon ratio, resulting in low-conductivity and surface-polarization issues, which restricts battery of high-rate performance. Herein, the rich charge transport channels among CFx were constructed using a well-dispersed and highly-oriented carbon nanotube arrays (CNTA) to enhance high-rate performance in Li/CFx battery. The advantage of high-orientation lies in maintaining the appropriate van der Waals forces of this CNTA prepared by catalytic chemical vapor deposition (CCVD), which helps to avoid carbon nanotubes (CNT) entanglement and achieves good dispersion. Compared with conductive additives of commercial carbon nanotubes (CCNT) and super-P (CSP), CNTA effectively releases CFx surface-polarization favouring to Li+ diffusion. Therefore, battery performance was enhanced with reduced voltage delay and low impedance. At a discharge rate of 5 C, the Li/CFx battery using CNTA had a specific capacity of 697.32 mAh/g, while these batteries using CCNT and CSP lost discharge-performance. This highly-oriented CNTA enriches the conductive additives system of lithium primary batteries and provides a novel pathway for suppressing CFx polarization.

Thermal hazard evaluation of 18650 lithium-ion batteries at various discharge rates

Lithium-ion batteries (LIB) provide high energy density, low self-discharge rate, long cycle life, and superior suitability for a wide range of applications, such as portable electronic devices, electric vehicles, and renewable energy systems. In this investigation, we prepared 18650 LIB cells with various discharging rates (1C, 2C, 3C, and 4C) using specified conditions for static discharging experiment, and recorded the battery discharge current (Idis), discharge time (tdis), central surface maximum temperature (Tmax), temperature fluctuation, discharge capacity (Cdis), discharge energy (Wdis), and voltage at different time intervals. We studied the association between the discharge rate and the thermal stability of LIB specimens. In the discharge process, it was observed that operating at an increased discharge rate exhibited a direct correlation with a higher temperature rise. The findings indicate that batteries prepared with a higher discharge rate exhibit greater instability in terms of inherent property. During the 4C discharge rate, the Tmax, Cdis, and Wdis values were 96.6 °C, 3.117 Ah, and 9.021 Wh, respectively. These results indicate that a discharging rate of 4C is inappropriate for batteries, while the discharging rates of 1C, 2C, and 3C are suitable in terms of thermal stability.

Efficient Water Supply Scheduling in IoT Sector With Modified Exploration-Based Artificial Gorilla Troops Optimizer

The main contribution of the proposed work is to minimize the capacity of the canal region and functional step for the head gate of the supply canal depending on the canal constraint. Due to the communication and interconnection over the sensors in IoT, the required decision variables are obtained for the operation of water supply scheduling. Then, the proposed model utilizes several decision variables such as start time, and discharge rate. In various sections, the decision variables change from the head of the canal to the tail, which is also to be gradually decreased as well. To overcome this constraint, the Modified Exploration-based Artificial Gorilla Troops Optimizer (ME-AGTO) algorithm is proposed in this article, where the start time, and discharge rate is efficiently optimized. The newly developed ME-AGTO algorithm is applied for the two-way water supply and acquires the optimal scheduling of the water supply. Hence, the canal capacity is considered with optimized variables at different sections throughout the head and tail parts of the canal. Thus, the schedules are created for the inflow of water with the aid of the rotation period and head gate. The performance is estimated to obtain the desired results of less conveyance loss.

An Adaptive Energy Management Approach for Battery-Supercapacitor Hybrid Energy Storage System

Energy storage systems (ESS) are indispensable in daily life and have two types that can offer high energy and high power density. Hybrid energy storage systems (HESS) are obtained by combining two or more energy storage units to benefit both types. Energy management systems (EMS) are essential in ensuring HESS's reliability, high performance, and efficiency. One of the most critical parameters for EMS is the battery state of health (SoH). Continuous monitoring of the SoH provides essential information regarding the system's status, detects unusual performance degradations and enables planned maintenance, prevents system failures, helps keep efficiency at a consistently high level, and helps ensure energy security by reducing downtime. The SoH parameter depends on parameters such as Depth of Discharge (DoD), charge and discharge rate (C-Rate), and temperature. Optimal values of these parameters directly affect the lifetime and operating performance of the battery. The proposed Adaptive Energy Management System (AEMS) uses the SoH parameter of the battery as the control input. It provides optimal control by dynamically updating the C-Rate and DoD parameters. In addition, the supercapacitor integrated into the system with filter-based power separation prevents deep discharge of the batteries. Under the proposed AEMS control, HESS has been observed to generate 6.31% more energy than a system relying solely on batteries. This beneficial relationship between supercapacitors and batteries efficiently managed by AEMS opens new possibilities for advanced energy management in applications ranging from electric vehicles to renewable energy storage systems.