Search results for: neuropsychological test battery

Authors: Irshad U. Khan, Tanmay Paul, Murali Mohan Seepana

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This paper presents a study on synthesizing and characterizing a Copper oxide doped Carbon (CuO-C) electrocatalyst for the negative half-cell reactions of Vanadium Redox Flow Battery (VRFB). The CuO was synthesized using a microreactor. The electrocatalyst was characterized using X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Field Emission Scanning Electron Microscopy (SEM). The electrochemical performance was assessed by linear sweep voltammetry (LSV). The findings suggest that the synthesized CuO exhibited favorable crystallinity, morphology, and surface area, which reflects improved cell performance.

Keywords: ECSA, electrocatalyst, energy storage, Tafel

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Authors: M. A. Mamun, M. I. Khan, M. H. Sarker, K. A. Khan, M. Shajahan

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The study was carried out to investigate on an innovative invention, Pathor Kuchi Leaf (PKL) cell, which is fueled with PKL sap of widely available plant called Bryophyllum pinnatum as an energy source for use in PKL battery to generate electricity. This battery, a primary source of electricity, has several order of magnitude longer shelf-lives than the traditional Galvanic cell battery, is still under investigation. In this regard, we have conducted some experiments using various instruments including Atomic Absorption Spectrophotometer (AAS), Ultra-Violet Visible spectrophotometer (UV-Vis), pH meter, Ampere-Volt-Ohm Meter (AVO Meter), etc. The AAS, UV-Vis, and pH-metric analysis data provided that the potential and current were produced as the Zn electrode itself acts as reductant while Cu2+ and H+ ions are behaving as the oxidant. The significant influence of secondary salt on current and potential leads to the dissociation of weak organic acids in PKL juice, and subsequent enrichment to the reactant ions by the secondary salt effects. However, the liquid junction potential was not as great as minimized with the opposite transference of organic acid anions and H+ ions as their dissimilar ionic mobilities. Moreover, the large value of the equilibrium constant (K) implies the big change in Gibbs free energy (∆G), the more electromotive force works in electron transfer during the forward electrochemical reaction which coincides with the fast reduction of the weight of zinc plate, revealed the additional electrical work in the presence of PKL sap. This easily fabricated high-performance PKL battery can show an excellent promise during the off-peak across the countryside.

Keywords: Atomic Absorption Spectrophotometer (AAS), Bryophylum Pinnatum Leaf (BPL), electricity, electrochemistry, organic acids

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: battery state estimation, hybrid electric vehicle, hybrid energy storage, state of charge, state of health

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Authors: Andrei Contan, Richard Torkar

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Aim: The process of test automation and its practices in industry have to be better understood, both for the industry itself and for the research community. Method: We conducted a quantitative industry survey by asking IT professionals to answer questions related to the area of test automation. Results: Test automation needs and practices vary greatly between organizations at different stages of the software development life cycle. Conclusions: Most of the findings are general test automation challenges and are specific to small- to medium-sized companies, developing software applications in the web, desktop or mobile domain.

Keywords: survey, testing, test automation, status of test automation

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Authors: Sandeep Das

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Terminal post is one of the most important features of a Battery. The design and manufacturing of post are very much critical especially when threaded inserts (Bolt-on type) are used since all the collected energy is delivered from the lead part to the threaded insert (Cu or Cu alloy). Any imperfection at the interface may cause Voltage drop, high resistance, high heat generation, etc. This may be because of sudden change of material properties from lead to Cu alloys. To avoid this problem, a scheme of material gradation is proposed for achieving continuous variation of material properties for the Post used in commercially available lead acid battery. The Functionally graded (FG) material for the post is considered to be composed of different layers of homogeneous material. The volume fraction of the materials used corresponding to each layer is calculated by considering its variation along the direction of current flow (z) according to a power law. Accordingly, the effective properties of the homogeneous layers are estimated and the Post composed of this FG material is modeled using the commercially available ANSYS software. The solid 186 layered structural solid element has been used for discretization of the model of the FG Post. A thermal electric analysis is performed on the layered FG model. The model developed has been validated by comparing the results of the existing Post model& experimental analysis

Keywords: ANSYS, functionally graded material, lead-acid battery, terminal post

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Authors: Sarish Rehman, Kishwar Khan, Yanglong Hou

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Among the existed myriad energy-storage technologies, lithium–sulfur batteries (LSBs) show the appealing potential for the ubiquitous growth of next-generation electrical energy storage application, owing to their unparalleled theoretical energy density of 2600 Wh/kg that is over five times larger than that of conventional lithium-ion batteries (LIBs). Despite its significant advances, its large scale implementations are plagued by multitude issues: particularly the intrinsic insulating nature of the sulfur (10-30 S/cm), mechanical degradation of the cathode due to large volume changes of sulfur up to 80 % during cycling and loss of active material (producing polysulfide shuttle effect). We design a unique structure, namely silicon/silica (Si/SiO2) crosslink with hierarchical porous carbon spheres (Si/SiO2@C), and use it as a new and efficient sulfur host to prepare Si/SiO2@C-S hybrid spheres to solve the hurdle of the polysulfides dissolution. As results of intriguing structural advantages developed hybrids spheres, it acts as efficient polysulfides reservoir for enhancing lithium sulfur battery (LSB) in the terms of capacity, rate ability and cycling stability via combined chemical and physical effects.

Keywords: high specific surface area, high power density, high content of sulfur, lithium sulfur battery

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Asser S. Abdelwahab, Nabil H. Abbasy, Ragi A. Hamdy

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Marine shipping has now become one of the major worldwide contributors to pollution and greenhouse gas emissions. Hybrid ships technology based on multiple energy sources has taken a great scope of research to get rid of ship emissions and cut down fuel expenses. Insufficiency between power generated and the demand load to withstand the transient behavior on ships during severe climate conditions will lead to a blackout. Thus, an efficient energy management system (EMS) is a mandatory scope for achieving higher system efficiency while enhancing the lifetime of the onboard storage systems is another salient EMS scope. Considering energy storage system conditions, both the battery state of charge (SOC) and temperature represent important parameters to prevent any malfunction of the storage system that eventually degrades the whole system. In this paper, a two battery packs ratio fuzzy logic control model is proposed. The overall aim is to control the charging/discharging current while including both the battery SOC and temperature in the energy management system. The full designs of the proposed controllers are described and simulated using Matlab. The results prove the successfulness of the proposed controller in stabilizing the system voltage during both loading and unloading while keeping the energy storage system in a healthy condition.

Keywords: energy storage system, power shipboard, hybrid ship, thermal runaway

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Authors: Mohammad Alipour, Ekin Esen, Riza Kizilel

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Lithium-ion batteries are a commonly used type of rechargeable batteries because of their high specific energy and specific power. With the growing popularity of electric vehicles and hybrid electric vehicles, increasing attentions have been paid to rechargeable Lithium-ion batteries. However, safety problems, high cost and poor performance in low ambient temperatures and high current rates, are big obstacles for commercial utilization of these batteries. By proper thermal management, most of the mentioned limitations could be eliminated. Temperature profile of the Li-ion cells has a significant role in the performance, safety, and cycle life of the battery. That is why little temperature gradient can lead to great loss in the performances of the battery packs. In recent years, numerous researchers are working on new techniques to imply a better thermal management on Li-ion batteries. Keeping the battery cells within an optimum range is the main objective of battery thermal management. Commercial Li-ion cells are composed of several electrochemical layers each consisting negative-current collector, negative electrode, separator, positive electrode, and positive current collector. However, many researchers have adopted a single-layer cell to save in computing time. Their hypothesis is that thermal conductivity of the layer elements is so high and heat transfer rate is so fast. Therefore, instead of several thin layers, they model the cell as one thick layer unit. In previous work, we showed that single-layer model is insufficient to simulate the thermal behavior and temperature nonuniformity of the high-capacity Li-ion cells. We also studied the effects of the number of layers on thermal behavior of the Li-ion batteries. In this work, first thermal and electrochemical behavior of the LiFePO₄ battery is modeled with 3D multilayer cell. The model is validated with the experimental measurements at different current rates and ambient temperatures. Real time heat generation rate is also studied at different discharge rates. Results showed non-uniform temperature distribution along the cell which requires thermal management system. Therefore, aluminum plates with mini-channel system were designed to control the temperature uniformity. Design parameters such as channel number and widths, inlet flow rate, and cooling fluids are optimized. As cooling fluids, water and air are compared. Pressure drop and velocity profiles inside the channels are illustrated. Both surface and internal temperature profiles of single cell and battery packs are investigated with and without cooling systems. Our results show that using optimized Mini-channel cooling plates effectively controls the temperature rise and uniformity of the single cells and battery packs. With increasing the inlet flow rate, cooling efficiency could be reached up to 60%.

Keywords: lithium ion battery, 3D multilayer model, mini-channel cooling plates, thermal management

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Authors: Raj Kumar Rajak, Bharat Mishra

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Bio-batteries represent an entirely new long-term, reasonable, reachable and ecofriendly approach to produce sustainable energy. In the present experimental work, we have studied the effect of generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow dung as an electrolyte. C-Mg electrode pair shows maximum voltage and SCC (Short Circuit Current) while C-Zn electrode pair shows less OCV (Open Circuit Voltage) and SCC. We have chosen C-Zn electrodes because Mg electrodes are not economical. By the studies of different electrodes and cow dung, it is found that C-Zn electrode battery is more suitable. This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: bio-batteries, electricity, cow-dung, electrodes, non-conventional

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Authors: Cian O'Shea, Ross O'Halloran, Peter Haigh

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Wireless Sensor Networks (WSN) are Internet of Things (IoT) edge devices. They are becoming widely adopted in many industries, including health care, building energy management, and conditional monitoring. As the scale of WSN deployments increases, the cost and complexity of battery replacement and disposal become more significant and in time may become a barrier to adoption. Harvesting ambient energies provide a pathway to reducing dependence on batteries and in the future may lead to autonomously powered sensors. This work describes a simulation tool that enables the user to predict the battery life of a wireless sensor that utilizes energy harvesting to supplement the battery power. To create this simulator, all aspects of a typical WSN edge device were modelled including, sensors, transceiver, and microcontroller as well as the energy source components (batteries, solar cells, thermoelectric generators (TEG), supercapacitors and DC/DC converters). The tool allows the user to plug and play different pre characterized devices as well as add user-defined devices. The goal of this simulation tool is to predict the lifetime of a device and scope for extension using ambient energy sources.

Keywords: Wireless Sensor Network, IoT, edge device, simulation, solar cells, TEG, supercapacitor, energy harvesting

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Authors: Zeinab Sanaee, Hossein Jafaripour

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Copper is an excellent conductive material that is widely used in the energy devices such as Lithium-ion batteries and supercapacitors as the current collector. On the other hand, copper oxide nanowires have been used in these applications as potential electrode material. In this paper, nanowires of Copper and Copper oxide have been synthesized through a simple and time and cost-effective approach. The thermally grown Copper oxide nanowires have been converted into Copper nanowires through annealing in the Hydrogen atmosphere in a DC-PECVD system. To have a proper Copper nanostructure formation, an Au nanolayer was coated on the surface of Copper oxide nanowires. The results show the successful achievement of Copper nanowires without deformation or cracking. These structures have a great potential for Lithium-ion batteries and supercapacitors.

Keywords: Copper, Copper oxide, nanowires, Hydrogen annealing, Lithium ion battery

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Authors: Argyris Karapetsas, Maria Bampou, Andriani Mitropoulou

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The aim of the present work is to study the role of brain function in social awareness processing. Mind controls all the psychosomatic functions. Mind’s functioning enables individual not only to recognize one's own self and propositional attitudes, but also to assign such attitudes to other individuals, and to consider such observed mental states in the elucidation of behavior. Participants and Methods: Twenty (n=20) undergraduate students (mean age 18 years old) were involved in this study. Students participated in a clinical assessment, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Assessment included both electrophysiological (i.e.Event Related Potentials (ERPs) esp.P300 waveform) and neuropsychological tests (Raven's Progressive Matrices (RPM) and Sally-Anne test). Results: Initial assessment’s results confirmed statistically significant differences between the males and females, as well as in score performance to the tests applied. Strong correlations emerged between prefrontal lobe functioning, RPM, Sally-Anne test and P300 latencies. Also, significant dysfunction of mind has been found, regarding its three dimensions (straight, circular and helical). At the end of the assessment, students received consultation and appropriate guidelines in order to improve their intrapersonal and interpersonal skills. Conclusions: Mind and social awareness phenomena play a vital role in human development and may act as determinants of the quality of one’s own life. Meanwhile, brain function is highly correlated with social awareness and it seems that different set of brain structures are involved in social behavior.

Keywords: brain activity, emotions, ERP's, social awareness

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Authors: Kamyar Maleki Bagherabadi, Torstein Aarseth Bø, Truls Flatberg, Olve Mo

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Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy, and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishery vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a PEM fuel cell, a diesel genset, and a battery. The methodologies used are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed, and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider time variation of the load provide more realistic estimations of energy and fuel consumption regarding hydrogen tank and battery size, still within low computational time.

Keywords: fuel cell, battery, hydrogen, hybrid power system, power management system

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Authors: Disha Gupta

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The aim of this research is to conduct X-ray and e-beam characterization techniques on lithium-ion battery materials for the improvement of battery performance. The key characterization techniques employed are the synchrotron X-ray Absorption Spectroscopy (XAS) combined with X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to obtain a more holistic approach to understanding material properties. This research effort provides additional battery characterization knowledge that promotes the development of new cathodes, anodes, electrolyte and separator materials for batteries, hence, leading to better and more efficient battery performance. Both ex-situ and in-situ synchrotron experiments were performed on LiFePO₄, one of the most common cathode material, from different commercial sources and their structural analysis, were conducted using Athena/Artemis software. This analysis technique was then further extended to study other cathode materials like LiMnxFe(₁₋ₓ)PO₄ and even some sulphate systems like Li₂Mn(SO₄)₂ and Li₂Co0.5Mn₀.₅ (SO₄)₂. XAS data were collected for Fe and P K-edge for LiFePO4, and Fe, Mn and P-K-edge for LiMnxFe(₁₋ₓ)PO₄ to conduct an exhaustive study of the structure. For the sulphate system, Li₂Mn(SO₄)₂, XAS data was collected at both Mn and S K-edge. Finite Difference Method for Near Edge Structure (FDMNES) simulations were also conducted for various iron, manganese and phosphate model compounds and compared with the experimental XANES data to understand mainly the pre-edge structural information of the absorbing atoms. The Fe K-edge XAS results showed a charge compensation occurring on the Fe atom for all the differently synthesized LiFePO₄ materials as well as the LiMnxFe(₁₋ₓ)PO₄ systems. However, the Mn K-edge showed a difference in results as the Mn concentration changed in the materials. For the sulphate-based system Li₂Mn(SO₄)₂, however, no change in the Mn K-edge was observed, even though electrochemical studies showed Mn redox reactions.

Keywords: li-ion batteries, electrochemistry, X-ray absorption spectroscopy, XRD

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Authors: Supachai Supmak, Yachai Limpiyakorn

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Mutation testing can be applied for the quality assessment of test cases. Prioritization of mutation test generation has been a critical element of the industry practice that would contribute to the evaluation of test cases. The industry generally delivers the product under the condition of time to the market and thus, inevitably sacrifices software testing tasks, even though many test cases are required for software verification. This paper presents an approach of applying a social network centrality measure, PageRank, to prioritize mutation test generation. The source code with the highest values of PageRank will be focused first when developing their test cases as these modules are vulnerable to defects or anomalies which may cause the consequent defects in many other associated modules. Moreover, the approach would help identify the reducible test cases in the test suite, still maintaining the same criteria as the original number of test cases.

Keywords: software testing, mutation test, network centrality measure, test case prioritization

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Authors: Rungrawee Samawathdana, Aim-Utcha Wattanaburanon

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Test specifications for open book or notes exams provide the essential information to identify the types of the test items with validity of the evaluations process. This article explains the purpose of test specifications and illustrates how to use it to help construct the approach of open book or notes exams. The complication of the course objectives is challenging for the test designing.

Keywords: course curriculum, environment for health, internationalization, test specifications

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Authors: Ziyan Zhang

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Although the Synthetic Control Method (SCM) is now widely applied, its most commonly- used inference method, placebo test, is often problematic, especially when the treatment is not uniquely assigned. This paper discusses the problems with the placebo test under the multivariate treatment case. And, to improve the power of inferences, I further propose an Andrews-type procedure as it potentially solves some drawbacks of the placebo test. Simulations are conducted to show the Andrews’ test is often valid and powerful, compared with the placebo test.

Keywords: Synthetic Control Method, Multiple treatments, Andrews' test, placebo test

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Authors: Swapnil Singh, Sanjoy Das

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Mobile Ad-Hoc Network (MANET) is infrastructure less networks dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depends on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper, we survey various energy efficient routing protocol. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.

Keywords: delaunay triangulation, deployment, energy efficiency, MANET

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Authors: Rozi Laskaraki, Argyris Karapetsas, Aikaterini Karapetsa

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This paper is focused on the efficacy of a rehabilitation program based on musical activities, implied to a group of school-aged dyslexic children. Objective: The purpose of this study was to investigate the efficacy of auditory training including musical exercises in children with developmental dyslexia (DD). Participants and Methods: 45 third-, and fourth-grade students with DD and a matched control group (n=45) were involved in this study. In the beginning, students participated in a clinical assessment, including both electrophysiological (i.e., event related potentials (ERPs) esp.P300 waveform) and neuropsychological tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Initial assessment’s results confirmed statistically significant lower performance for children with DD, compared to that of the typical readers. After clinical assessment, a subgroup of children with dyslexia was submitted to a music auditory training program, conducted in 45-minute training sessions, once a week, for twenty weeks. The program included structured and digitized musical activities involving pitch, rhythm, melody and tempo perception and discrimination as well as auditory sequencing. After the intervention period, children underwent a new recording of ERPs. Results: The electrophysiological results revealed that children had similar P300 latency values to that of the controls, after the remediation program; thus children overcame their deficits. Conclusion: The outcomes of the current study suggest that ERPs is a valid clinical tool in neuropsychological assessment settings and dyslexia can be ameliorated through music auditory training.

Keywords: dyslexia, event related potentials, learning disabilities, music, rehabilitation

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Authors: Umran Kurtan, Hamide Aydin, Sevim Unugur Celik, Ayhan Bozkurt

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In the present work, novel hBN/polyacrylonitrile composite nanofibers were produced via electrospinning approach and loaded with the electrolyte for rechargeable lithium-ion battery applications. The electrospun nanofibers comprising various hBN contents were characterized by using Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The influence of hBN/PAN ratios onto the properties of the porous composite system, such as fiber diameter, porosity, and the liquid electrolyte uptake capability were systematically studied. Ionic conductivities and electrochemical characterizations were evaluated after loading electrospun hBN/PAN composite nanofiber with liquid electrolyte, i.e., 1 M lithium hexafluorophosphate (LiPF6) in ethylene carbonate (EC)/ethyl methyl carbonate (EMC) (1:1 vol). The electrolyte loaded nanofiber has a highest ionic conductivity of 10−3 S cm⁻¹ at room temperature. According to cyclic voltammetry (CV) results it exhibited a high electrochemical stability window up to 4.7 V versus Li+/Li. Li//10 wt% hBN/PAN//LiCO₂ cell was produced which delivered high discharge capacity of 144 mAhg⁻¹ and capacity retention of 92.4%. Considering high safety and low cost properties of the resulting hBN/PAN fiber electrolytes, these materials can be suggested as potential separator materials for lithium-ion batteries.

Keywords: hexagonal boron nitride, polyacrylonitrile, electrospinning, lithium ion battery

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Authors: Jan Karl, Ondrej Suchy, Eliska Fiserova, Milan Ruzicka

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The evolving electromobility and all the electronics also bring an increase of danger with used Li-batteries. Li-batteries have been used in many industries, and currently many types of the batteries are available. Batteries have different compositions that affect their behavior. In the field of Li-battery safety, there are some areas of little discussion, such as extinguishing of fires caused by Li-batteries as well as toxicity of gaseous compounds released from Li batteries, transport or storage. Technical Institute of Fire Protection, which is a part of Fire Brigades of the Czech Republic, is dealing with the safety of Li batteries. That is the reason why we are dealing with toxicity of gaseous compounds released under conditions of fire, mechanical damage, overcharging and other emergencies that may occur. This is necessary for protection of intervening of fire brigade units, people in the vicinity and other envirnomental consequences. In this work, different types of batteries (Li-ion, Li-Po, LTO, LFP) with different kind of damage were tested, and the toxicity and total amount of released gases were studied. These values were evaluated according to their environmental hazard. FTIR spectroscopy was used for the evaluation of toxicity. We used a FTIR gas cell for continuous measurement. The total amount of released gases was determined by collecting the total gas phase through the absorbers and then determining the toxicants absorbed into the solutions. Based on the obtained results, it is possible to determine the protective equipment necessary for the event of an emergency with a Li-battery, to define the environmental load and the immediate danger in an emergency.

Keywords: Li-battery, toxicity, gaseous toxic compounds, FTIR spectroscopy

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

Abstract:

Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Wenxin Mei, Jinhua Sun, Qingsong Wang

Abstract:

The volume expansion of lithium-ion batteries is mainly induced by intercalation induced stress within the negative electrode, resulting in capacity degradation and even battery failure. Stress generation due to lithium intercalation into graphite particles is investigated based on an electrochemical-mechanical model in this work. The two-dimensional model presented is fully coupled, inclusive of the impacts of intercalation-induced stress, stress-induced intercalation, to evaluate the lithium concentration, stress generation, and displacement intra and inter-particle. The results show that the distribution of lithium concentration and stress exhibits an analogous pattern, which reflects the relation between lithium diffusion and stress. The results of inter-particle stress indicate that larger Von-Mises stress is displayed where the two particles are in contact with each other, and deformation at the edge of particles is also observed, predicting fracture. Additionally, the maximum inter-particle stress at the end of lithium intercalation is nearly ten times the intraparticle stress. And the maximum inter-particle displacement is increased by 24% compared to the single-particle. Finally, the effect of graphite particle arrangement on inter-particle stress is studied. It is found that inter-particle stress with tighter arrangement exhibits lower stress. This work can provide guidance for predicting the intra and inter-particle stress to take measures to avoid cracking of electrode material.

Keywords: electrochemical-mechanical model, graphite particle, lithium concentration, lithium ion battery, stress

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Authors: Gabouze Nourredine, Saloua Merazga

Abstract:

Due to their exceptional durability, low-cost, high-power density, and reliability, cathodes based on titanium dioxide, and more specifically spinel LTO (Li4Ti5O12), present an attractive alternative to conventional lithium cathode materials for multiple applications. The aim of this work is to synthesize and characterize the nanopowders of titanium dioxide (TiO₂) and lithium titanate (Li₄Ti5O₁₂) by the hydrothermal method and to use them as a cathode in a lithium-ion battery. The structural and morphological characterizations of the synthesized powders were performed by XRD, SEM, EDS, and FTIR-ATR. Nevertheless, the study of the electrochemical performances of the elaborated electrode materials was carried out by: cyclic voltametry (CV) and galvanostatic charge/discharge (CDG). The prepared electrode by the powder annealed at 800 °C has a good specific capacity of about 173 mAh/g and a good cyclic stability

Keywords: lithuim-ion, battery, LTO, tio2, capacity

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Authors: Farnaz Fotovvatikhah, Javad Akbari

Abstract:

Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

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Authors: Z. S. Yip, T. K. Tan, C. C. Geh, T. T. Ting

Abstract:

The mobile phone is an indispensable device in today’s daily living. The arising new brands in the market with different specification are targeting at the different population. The most promising market would be the younger generation who are IT savvy. Therefore, it is beneficial to find out their factors of consideration in purchasing a mobile phone. A survey is carried out in Malaysia to discover the current youngster’s mobile phone buying behavior. This study has found that the most influencing factor of consideration is Price, followed by Feature, and Battery Lifespan. Gender and Income have no relationship with certain factors of consideration. It is important to discover the factors of consideration in order to provide industry insight into the current trend of smartphone in Malaysia.

Keywords: buying behavior, smart phone, mobile brand, mobile operating system, specification, battery lifespan

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Authors: SeungHee Ryu, Junil Moon

Abstract:

The magnetic resonance wireless power transfer system is widely researched due to its benefits such as spatial freedom. In this paper, power transmitting unit and power receiving unit of wireless battery charger for mobile devices is presented. Power transmitting unit efficiency is measured under different test conditions with power receiving units.

Keywords: magnetic resonance coupling, wireless power transfer, power transfer efficiency.

Procedia PDF Downloads 508

Authors: Wesley Teskey, Vedran Glavas, Julian Wegener

Abstract:

Generating battery cathode microstructures is an important area of research, given the proliferation of the use of automotive batteries. Currently, finite element analysis (FEA) is often used for simulations of battery cathode microstructures before physical batteries can be manufactured and tested to verify the simulation results. Unfortunately, a key drawback of using FEA is that this method of simulation is very slow in terms of computational runtime. Generative AI offers the key advantage of speed when compared to FEA, and because of this, generative AI is capable of evaluating very large numbers of candidate microstructures. Given AI generated candidate microstructures, a subset of the promising microstructures can be selected for further validation using FEA. Leveraging the speed advantage of AI allows for a better final microstructural selection because high speed allows for the evaluation of many more candidate microstructures. For the approach presented, battery cathode 3D candidate microstructures are generated using Gaussian Mixture Models (GMMs) and pix2pix. This approach first uses GMMs to generate a population of spheres (representing the “active material” of the cathode). Once spheres have been sampled from the GMM, they are placed within a microstructure. Subsequently, the pix2pix sweeps over the 3D microstructure (iteratively) slice by slice and adds details to the microstructure to determine what portions of the microstructure will become electrolyte and what part of the microstructure will become binder. In this manner, each subsequent slice of the microstructure is evaluated using pix2pix, where the inputs into pix2pix are the previously processed layers of the microstructure. By feeding into pix2pix previously fully processed layers of the microstructure, pix2pix can be used to ensure candidate microstructures represent a realistic physical reality. More specifically, in order for the microstructure to represent a realistic physical reality, the locations of electrolyte and binder in each layer of the microstructure must reasonably match the locations of electrolyte and binder in previous layers to ensure geometric continuity. Using the above outlined approach, a 10x to 100x speed increase was possible when generating candidate microstructures using AI when compared to using a FEA only approach for this task. A key metric for evaluating microstructures was the battery specific power value that the microstructures would be able to produce. The best generative AI result obtained was a 12% increase in specific power for a candidate microstructure when compared to what a FEA only approach was capable of producing. This 12% increase in specific power was verified by FEA simulation.

Keywords: finite element analysis, gaussian mixture models, generative design, Pix2Pix, structural design

Procedia PDF Downloads 102