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Hybrid renewable electric energy generation system become essential to the most of electric networks and the stand-alone systems like the water pumping and telecommunication systems. The renewable sources usually required storage system due to change in the power outputs during the day. Due to increase in demand of using batteries, the charging process of battery system needed to be well managed through an adaptive controlled energy managing system. In this paper a standalone system using photovoltaic, wind generation, fuel cell and storage batteries are contributed in supplying the desired load and the charging balance of batteries is achieved by using AI techniques to enhance battery charging controller performance. The main goal of this paper is to design and implement an integrated smart artificial controller, this controller is responsible for controlling both the battery charge voltage using the boost converter and the other controller is to control the charging current of the battery through DC to DC converter using (ANFIS) and (GA) techniques. This study is implemented using MATLAB /Simulink and the results are presented to show the applicability and effieciency of the proposed technique. [ABSTRACT FROM AUTHOR]

This study investigated the influence of battery charge levels on the stability of lightemitting diode (LED) curing-light intensity by measuring the intensity from fully charged through fully discharged batteries. The microhardness of resin composites polymerized by the light-curing units at various battery charge levels was measured. The light intensities of seven fully charged battery LED lightcuring units--1) LY-A180, 2) Bluephase, 3) Woodpecker, 4) Demi Plus, 5) Saab II, 6) Elipar S10, and 7) MiniLED--were measured with a radiometer (Kerr) after every 10 uses (20 seconds per use) until the battery was discharged. Ten 2-mm-thick cylindrical specimens of A3 shade nanofilled resin composite (PREMISE, Kerr) were prepared per LED light-curing unit group. Each specimen was irradiated by the fully charged light-curing unit for 20 seconds. The LED light-curing units were then used until the battery charge fell to 50%. Specimens were prepared again as described above. This was repeated again when the light-curing units' battery charge fell to 25% and when the light intensity had decreased to 400 mW/cm². The top/bottom surface Knoop hardness ratios of the specimens were determined. The microhardness data were analyzed by one-way analysis of variance with Tukey test at a significance level of 0.05. The Pearson correlation coefficient was used to determine significant correlations between surface hardness and light intensity. We found that the light intensities of the Bluephase, Demi Plus, and Elipar S10 units were stable. The intensity of the MiniLED unit decreased slightly; however, it remained above 400 mW/cm². In contrast, the intensities of the LY-A180, Woodpecker, and Saab II units decreased below 400 mW/cm². There was also a significant decrease in the surface microhardnesses of the resin composite specimens treated with MiniLED, LY-A180, Woodpecker, and Saab II. In conclusion, the light intensity of several LED light-curing units decreased as the battery was discharged, with a coincident reduction in the units' ability to polymerize resin composite. Therefore, the intensity of an LED light-curing unit should be evaluated during the life of its battery charge to ensure that sufficient light intensity is being generated. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The lead-acid battery experimental testing platform in energy storage power station is composed of the WEBEST valve-controlled sealed colloid lead-acid battery and the bidirectional high-precision programmable DC power supply so as to control the battery charge and discharge, which can realize the information collection, data processing and signal control. Based on the established experimental testing platform, the performance testing experiments on the lead-acid battery are carried out in details. The charge and discharge experiments under the different working conditions of lead-acid batteries are carried out to analyze the characteristics of charge and discharge of lead-acid battery. On the other hand, according to the above discussed battery charge and discharge characteristics, the remaining power of the situation of the energy storage power station under the complicated working conditions is estimated. Through the related performance testing experiments, the established accurate cell model can effectively improve the accuracy of estimating the remaining power of the battery. [ABSTRACT FROM AUTHOR]

This article reports on a study from the Oak Ridge National Laboratory which claims that titanium dioxide creates a material that increases surface area and features a charge-discharge capability for lithium-ion batteries.

The paper describes an original architecture aimed at tracking assets within construction sites. The main components are Radio Frequency IDentification (RFID), Bluetooth Low Energy (BLE) tags and smartphones. The core functions are performed by two Android applications, which implement asset tracking and searching. The main merits of the architecture are its ability to maximize smartphone battery lifetime, that can reach an entire working shift, very satisfactory accuracy of BLE tag-smartphone distance estimation (with a mean error around 2 [m]), high probability of detecting all the tags present in the construction site, as well as a suitably short Aging time. [ABSTRACT FROM AUTHOR]

Methods for battery state and parameter estimation have been widely investigated, while the achievable accuracy of the estimation remains a critical but somehow overlooked topic. In this paper, the analytic bounds on the accuracy of battery state and parameter estimation accounting for voltage measurement noises are derived based on the Fisher information matrix and Cramer-Rao bound analysis. The state and parameters under discussion include the state of charge, capacity and (ohmic) resistance. The estimation accuracy is influenced by the information contained in the data set used for estimation. It is found that the main contributing factors to the accuracy of SOC estimation are the slope of the OCV curve and number of data points, while the accuracy of capacity estimation is affected by both OCV slope and SOC variation, and that of resistance estimation depends heavily on the current magnitude. The analytic bounds are derived for both standalone estimation, where only one state/parameter is estimated, and combined estimation where they are estimated together. The loss of accuracy in combined estimation compared to standalone estimation is usually expected. However, when the current excitation satisfies certain patterns, such loss can be avoided. The conclusions can be used as guidelines for offline experiment design as well as online evaluation of the accuracy of adaptive state and parameter estimation. [ABSTRACT FROM AUTHOR]

• Magnesium and magnesium alloys deposited by thermionic vacuum arc. • Amorphous thin film deposition with smooth surfaces. • Laser-induced method increases the crystallinity of the deposited thin films. • Both methods allow the alloying process with other materials as Ag, Zn, C. • The thermal energy during photonic processes increases the local temperature variation. Magnesium and magnesium thin alloy films were deposited using a thermionic vacuum arc (TVA), which has multiple applications in the field of metallic electrodes for diodes and batteries or active corrosion protection. An improved laser-induced TVA (LTVA) method favors the crystallization processes of the deposited magnesium-based films because the interaction between laser and plasma discharge changes the thermal energy during photonic processes due to the local temperature variation. Plasma diagnosis based on current discharge measurements suggests an inelastic collision between the laser beam and the atoms from the plasma discharge. The morphology and surface properties of the obtained thin films differ between these two methods. While the amorphous character is dominant for TVA thin films, enabling a smooth surface, the LTVA method produces rough surfaces with prominent crystallinity, less hydrophobic character and lower surface energy. The smooth surfaces obtained by the TVA methods produce metallic electrodes with good electrical contact, ensuring better diodes and battery charge transport. Both methods allow uniform magnesium alloys to be obtained, but the laser used in the LTVA on the discharge plasma controls the added metal or element ratio. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy and environmental concerns have fostered the era of electric vehicles (EVs) to take over and be welcomed more than ever. Fuel-powered vehicles are still predominant; however, this trend appears to be changing sooner than we might expect. Countries in Europe, Asia, and many states in America have already made the decision to transition to a fully EV industry in the next few years. This looks promising; however, drivers still have concerns about the battery mileage of such vehicles and the anxiety that such driving experiences! Indeed, driving with the probability of having insufficient battery charge that may be involved in guaranteeing the delivery to the trip destination imposes a level of anxiety on the vehicle drivers. Therefore, for an alternative to traditional fuel-powered vehicles to be convincing, there needs to be sufficient coverage of charging stations to serve cities in the same way that fuel stations serve traditional vehicles. The current navigation models select routes based solely on distance and traffic metrics, without taking into account the coverage of fuel service stations that these routes may offer. This assumption is made under the belief that all routes are adequately covered. This might be true for fuel-powered vehicles, but not for EVs. Hence, in this work, we are presenting AFARM, a routing model that enables a smart navigation system specifically designed for EVs. This model routes the EVs via paths that are lined with charging stations that align with the EV's current charge requirements. Different from the other models proposed in the literature, AFARM is autonomous in the sense that it determines navigation paths for each vehicle based on its make, model, and current battery status. Moreover, it employs Dijkstra's algorithm to accommodate varying least-cost navigation preferences, ranging from shortest-distance routes to routes with the shortest trip time and routes with maximum residual battery capacities as well. According to the EV driver's preference, AFARM checks the set of candidate paths at the source point and selects the appropriate path for the vehicle to drive based on its current status. Consequently, AFARM provides an anxiety-free navigation model that allows for a reliable and environmentally friendly driving experience, promoting this alternative mode of transportation. [ABSTRACT FROM AUTHOR]

The accelerated adoption of Electric Vehicles (EVs) necessitates innovative and effective pricing strategies for charging infrastructure. This study leverages the MATSim (Multi-Agent Transport Simulation) framework to meticulously evaluate the performance of two distinctive EV charging pricing models: time-based charging and a hybrid model integrating both usage-based and time-based components. Driven by the pivotal question of how EV charging should be optimally priced—whether contingent on energy consumption or charging duration—the research endeavors to conduct two simulations. These simulations aim to provide a comprehensive comparative analysis, evaluating metrics such as total power derived from grids, utility revenue, charging station queues and served vehicles. In the time-based charging scenario, EVs incur charges based on their plugged-in duration, reflecting a pricing approach that correlates directly with the time a vehicle remains connected to the charging station. In contrast, in the hybrid model, EVs undergo initial billing based on usage until a predetermined battery charge point is reached, such as achieving a full battery. Subsequently, time-based pricing takes effect until the user disconnects the vehicle. The findings indicate that, in the combined approach, utility owners have the potential to generate more revenue. Conversely, the time-based approach demonstrates a capacity to serve a higher number of electric EVs, with comparable queue lengths observed in both approaches. Importantly, using the results of this paper, policymakers can suggest pricing schemes that maximize benefits for utility owners, reduce queues at charging stations, and ensure the security of power grids. [ABSTRACT FROM AUTHOR]

The aim of this study is to model the brushless direct current motors and regenerative braking system used in electric vehicles using intelligent control approaches. Type-2 fuzzy logic control model is used as an intelligent control method. The application of regenerative braking extends the driving range of electric vehicles. In this study, an innovative regenerative braking system is presented. Speed control of brushless direct current motor and control of regenerative braking system are provided by Type-2 fuzzy logic control. Type-2 fuzzy logic control outperforms other solutions in terms of modeling uncertainties, generating new solutions, robustness, and efficiency. Type-2 fuzzy logic control is built on Matlab/M-file platform. The simulation in which the experimental studies were carried out was created on the MATLAB/Simulink platform. With this simulation study, battery charge status, battery current and brushless direct current motor speed values were obtained. The simulation results show that Type-2 fuzzy logic control can effectively control regenerative braking system. The regenerative braking system maintains its braking quality, while the electric vehicle slows it down at a safe driving distance. In addition, it is clearly seen in the results that the brushless direct current motor in the electric vehicle can increase the driving distance by charging the vehicle battery, thanks to its use as an alternator during braking. [ABSTRACT FROM AUTHOR]

The increase of using electric vehicles (EVs) may increase power demand and therefore major effects on the power system. Therefore, if we do not have an appropriate program for utilizing and managing battery charging in the EVs, the charging process may coincide with the peak of power consumption and cause severe network problems. This paper deals with modeling the problem and estimating load consumption in EVs connected to the system. The EVs have been considered based on a random load and a probabilistic process. To manage the EVs, a traffic method called the spatial–temporal scheme, which uses the Monte Carlo algorithm, has been proposed. Also, the proposed method can be used to represent a model of electric vehicles changes in their battery charge and their need for charging at different times of a full day in different zones of the city. The proposed method has been simulated in the Matlab software and implemented for Hamedan province. The results show that using this method of estimation can improve the management of EVs. • The vehicle's behavior across the city is simulated using Hamadan's urban traffic data. • Battery charge changes and need for charging at different times of a full day in different zones of the city are then calculated. • The estimation of EV's charging value per hour and in each area in network has been shown. • The results show that using the estimating method can be reduced the consume fuel of EVs. [ABSTRACT FROM AUTHOR]

The article titled "Detection range, height, and cloud cover effects on signal strength of HybridTag radio transmitters on birds" discusses the use of automated radio telemetry to track bird migration patterns and survivorship. The study focuses on the use of HybridTag radio transmitters manufactured by Cellular Tracking Technologies (CTT) and the importance of understanding the detection range and signal strength of these transmitters. The researchers conducted tests to determine how factors such as height, ambient light, and battery charge affect the signal strength of the transmitters. The results showed that signal strength detection varies with the level of battery charge. This research contributes to a better understanding of automated radio telemetry and accurate wildlife tracking technology. [Extracted from the article]

Accurate lithium-ion battery charge state estimation is crucial for battery management systems. Modeling of dual polarization--electrical equivalent circuit based on ternary lithium batteries as a research object, a variable forgetting factor recursive least square method is proposed for parameter identification given the insufficient tracking ability of the traditional recursive least squares method for abrupt and time-varying signals in a non- stationary environment. A backward smoothing square root cubature Kalman filtering algorithm is applied to enhance the accuracy and convergence speed of SOC estimation. The algorithm uses the square root update to ensure the numerical stability of the filtering and uses the idea of backward smoothing-forward filtering to improve the filtering accuracy on the basis of the first forward filtering. Finally, variable forgetting factor recursive least square is combined with backward smoothing square root cubature Kalman filtering to achieve the joint estimation of model parameters and state of charge, and the feasibility of the battery state of charge estimation is verified in different working conditions. The simulation results show that the variable forgetting factor recursive least square-backward smoothing square root cubature Kalman filter algorithm improves the study's filtering accuracy and convergence speed of lithium-ion batteries. [ABSTRACT FROM AUTHOR]

This paper focuses on experimented space projects run by universities, offering an effective design process to improve learning methods in space engineering. The approach used for the design of CubeSat Electrical Power System (EPS) will go through estimations, sizing, simulations, PCB design and end with an experimental test procedure for design validation. The main design criteria presented in this paper are low costs and effective reliability. To meet the first criterion, the Commercial-Off-The-Shelf (COTS) components are used during the design, which has become an effective path to put experimental payloads in orbit for minimal cost. In the second criterion, the function of some critical EPS components was replicated, such as circuits used for power maximization and battery charge regulation, by following a suitable algorithm embedded in MCU and hot/cold redundant analog integrated circuits. However, the choice was made on the state of the art of CubeSat components already tested. This approach of working will help new space engineers to think about optimal solutions for the design of the appropriate EPS for a CubeSat university project achievable on a limited budget. Finally, the necessary experiments of the designed EPS were carried out and the results were illustrated in the context below. [ABSTRACT FROM AUTHOR]

Integrating EVs (Electric Vehicles) with the electrical system presents essential load distribution difficulties because EV recharging structures are unpredictable and variable. The article presents an innovative technique employing multiple-agent deeper Q-Networking (MADQN) to coordinate electric automobiles and improve the electricity system balance of load. The suggested MADQN simulation rapidly optimizes battery charge plans by utilizing the capabilities of multiple agent networks as well as deeper reinforced learning. The framework adjusts to current network situations utilizing cooperative decision-making between substances, considering variables like a need for power, accessibility to green energy sources, and protection of the arrangement. Beneficial load distribution is made possible when reducing expenses and ecological damage because of the system's capacity to gather data from and modify intricate, changing circumstances. The findings from the modelling indicate how well the suggested MADQN method works to enhance network efficiency, lower peak usage, and use more sustainable power resources. These factors help build a more robust, adaptable, intelligent grid environment. • MADQN proposed to coordinate EVs and improve grid load balancing. • Optimizes charging plans using multi-agent systems and deep Q-learning. • Adapts to grid conditions via cooperative decision-making. • Enables efficient load distribution, reduces costs and environmental impact. • Improves grid efficiency, reduces peak demand, increases renewable energy use. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Estudos da Linguagem is the property of Revista de Estudos da Linguagem and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main objective of this research is to employ artificial neural networks in battery management systems (BMS), considering that one of the main applications of artificial neural networks is to operate as a function approximator, mapping the functional relationship between the variables of a system, from set known samples. In this context, this work approaches a method to predict the state of charge of batteries using techniques of artificial neural networks through a real database and models of the charge curve of real sodium—nickel chloride batteries. The behavior of the BMS is analyzed, using the models found in the output curves, in which the methodology used is implemented in the MATLAB® software to obtain the load curves. In this case, the proposed method uses a Multilayer Perceptron artificial neural network, which is a Feedforward architecture with backpropagation training algorithm. Finally, it was verified that the performance of the algorithm is closely linked with the adjustments in the number of layers. With the proper adjustments, the results expressed an excellent ability to indicate the battery charge status, as well as the analysis of the stipulated errors. Besides that, it is important to highlight that the methodology can be applied to other types of batteries, such as lithium battery. [ABSTRACT FROM AUTHOR]

The battery storage system of the integrated energy station contains electric vehicles as the distributed energy storage node of the regional power system can help the regional power system to achieve peak shaving and valley filling. This paper proposes a many-objective optimization based mutual feed model of the energy system of the integrated energy station. The model includes multiple modules of electric vehicle (EV), wind turbine (WT), photovoltaic (PV) and battery energy storage system (BESS). BESS was modeled according to the two behaviors of EVs charging and swapping. The model ensures the role of peak shaving and valley filling for regional power, reduces the loss of battery life in the battery storage system of the integrated energy station, and reduces the operating cost of the battery storage system. In the optimized results, the regional power system load peak-to-valley ratio by 28.72 %, and the daily battery charge/discharge life loss is minimized to 0.00036 %. In addition, for known many-objective optimization problems, this paper also proposes a new meta-heuristic many-objective optimization algorithm the non-dominated sorting hunter prey optimization (NSHPO for short) and compared with other four many-objective optimization algorithms by three indexes (Distribution range, Hypervolume index, and Running time). The simulation results show that compared with other algorithms, the HV metrics of NSHPO are lower by about 1.56 %-7.26 %, Spread metrics are better by about 0.39 %-2.73 %, and the proposed NSHPO algorithm is better in terms of convergence and distributivity. • The optimal scheduling model of energy management system of integrated energy station with electric vehicle is presented. • Proposed the non-dominated sorting hunter prey optimization (NSHPO). • Achieving peak-shaving and valley filling for the regional power system. • The optimal scheduling solution can effectively reduce operating costs. [ABSTRACT FROM AUTHOR]

Abstract During the Discontinuous Reception (DRX) mechanism, a User Equipment (UE) turns off most of its components for a prolonged period. The battery charge of a UE, which is a continuous quantity, arises as a fluid model. In this scenario, we represent the system as the reservoir where battery charge gets accumulated or is depleted gradually over the time, subject to a random environment constructed by the DRX mechanism. Therefore, the DRX mechanism acts as the background process for the fluid queue model of the battery charge. In a UE, battery charge available at any time t is considered as the fluid available in the reservoir. Different discharging rates are considered for the various states of the DRX mechanism. Using the fluid queue model, cumulative distribution function for the battery life of a DRX enabled UE is derived. Further, the expression for the mean battery life is obtained and analyzed numerically. [ABSTRACT FROM AUTHOR]

To explore the design of solar power management circuit, the fuzzy logic control algorithm based on MPPT, which has fast control speed and good environment robustness, is adopted as the control algorithm. In addition, the MPPT solar battery charge and discharge power management circuit is designed and successfully applied in the on-line measurement projects of dielectric loss of wireless sensor network in Jilin Province LG Electronics Company. The results show that the charging efficiency of solar battery charge and discharge power management circuit can reach above 80%, and the current of static power management circuit is less than 1mA. In different light intensities, the dynamic power management is intelligently carried out. At last, it is concluded that the stability and reliability of circuit are quite high. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

At this moment, non-aqueous rechargeable lithium-oxygen batteries (LOBs) with extremely high energy density are regarded as the most viable energy storage devices to potentially replace petroleum. One of the most crucial impediments to their implementation has been ensuring facile oxygen availability. Moreover, as semi-sealed systems, LOBs have confronted challenges including oxygen impurities, product degradation, anode corrosion, frequent side reactions, and mediocre cycling performance. In this work, utilizing the physical adsorption of porous (micro-, meso- and macro-porous) solid carbon materials, we incorporate an oxygen storage layer (OSL) with reversible oxygen ad/desorption capabilities into a LOB to develop novel fully-sealed lithium-oxygen batteries (F-S-LOBs). The results demonstrate mesoporous carbons exhibit optimal oxygen adsorption/desorption kinetics, rendering them highly suitable for F-S-LOBs without developing complex oxygen-permeable membranes or carrying oxygen tanks. The OSL fabricated with mesoporous carbon can sustain battery charge/discharge at various current densities with exceptional cycling performance. Additionally, we provide approximate pore size guidelines for oxygen storage materials to aid future research. This study is anticipated to offer a new robust research direction for metal-air batteries and to forge a new path toward promoting the commercialization and development of this technology. [Display omitted] • An unprecedented design concept: an all-enclosed metal-air battery. • Ultra-high volumetric specific energy (80 times that of traditional LOBs). • excellent cycling performance (more than 150 days). [ABSTRACT FROM AUTHOR]

The renewable sources integration with the DC micro grid is playing vital role in the current distribution system for providing the necessary clean power. The available of abundant renewable sources can be integrated through the DC link medium. The intermittent nature of renewable sources and dynamic switching of loads affects the quality of supply and DC link voltage respectively. It may fails to supply the power continuously. Reliability of power supply can be achieved with the use of integration of storage system. Here, the solar photovoltaic (SPV) array is fed with battery storage, fuel cell through the DC link medium. Utilizing SPV array maximum power is tracked using intelligent controller based maximum power point tracking (MPPT) technique. The battery storage with the DC link integration made through the bi-directional DC-DC converter with the help of the battery charge controller. Fuel cell is used as a base source and it's fed with the DC link system. Finally, the simulation of SPV array, battery storage with fuel cell integration is performed under dynamic switching of loads. The variations in the source and switching of load performance are simulated in the MATLAB/Simulation software. [ABSTRACT FROM AUTHOR]

The process of finding a route between the transmitter and the receiver node in the Mobile Adhoc Networks (MANets) is a renewed issue that is becoming more and more interesting to the researchers as this type of networks grow and expand. The dynamic nature of MANET and the limited capabilities of wireless nodes in terms of memory size and battery charge are the most important obstacles to the routing (path-finding) process between nodes. In this research, we introduced a new protocol based on the well-known DSR protocol. The proposed routing protocol adds a mechanism to control the RREQ Flooding process; this aims to reach more stable routes while reducing the overhead of routing process caused by link breakage between nodes, and reduces the overhead of network flooding with RREQ messages with each attempt to find a path. In this proposed mechanism, RREQ messages are sent to subset of the devices that are adjacent to the transmitter node, this selection depends on a stability evaluation criterion calculated based on three weighted factors: the speed of the node, the out-degree value (the number of adjacent nodes), and the number of tracks stored in the nodes' memory. The proportion of devices selected is automatically changed adaptively to ensure the achievement of the expected throughput for this network. The proposed protocol was tested using simulation where results showed that ASDSR proved an enhancement in route stability about (0.13), and a decrease in the number of deleted routes by (9%), while maintaining the expected packet delivery ratio of the original DSR by about (0.86). [ABSTRACT FROM AUTHOR]

Recent advancements in wearable technology have made kinetic and kinematic analysis of the throwing motion more accessible to recreational and professional baseball pitchers. Utilization of wearable technology to monitor the pitching motion has several potential applications for injury prevention and postinjury rehabilitation. However, the device must be properly applied to collect meaningful data. Erratic or inconsistent measurements can be caused by inadequate battery charge, incorrect sensor placement, and inadvertent motion capture of fielding maneuvers or other nonpitching throws. These problems can be overcome with a protocol that includes collecting biomechanical data in real time and routinely checking the sensor position throughout the duration of the throwing session. In this article, we outline our protocol for collecting biomechanical data and troubleshooting suboptimal device function during pitching sessions. [ABSTRACT FROM AUTHOR]

Cooperation is a central idea to the usage of swarm robotics. It enables the solution of complex problems with a coordinated execution of simple tasks by a large group of small robot, which together lead to the achievement of the swarm common goal. This coordination is only possible with an efficient task allocation. Inspired by the strategy of the particle swarm optimization algorithm, we propose a novel algorithm called the Clustered Dynamic Task Allocation. This algorithm performs task allocation in a swarm robotic system in a fully distributed manner. It performs a guided search of the allocation space using the concept of adaptive speed. This search process requires information exchange between robots. This robot communication process must be planned carefully so as to achieve two conflicting objectives: the knowledge acquired by a given robot must flow throughout the swarm so that the optimization process may converge yet this communication must be limited so it does not hinder the efficiency of the task allocation process regarding large swarms. This paper proposes the use of a clustered communication topology between the swarm robots, aiming to optimize the underlying communication process, and thus enabling efficient task allocation for large robotic swarms. The results obtained with the cluster-based topology are compared to those obtained with the full mesh-based topology. On average, the results show a clear improvement in terms of execution time and battery charge requirements. Moreover, the performance of the proposed algorithm and the stability of the produced allocation are compared to other well-known models, demonstrating its better applicability to real-world swarm robotics based systems. • We propose a novel approach to the Dynamic Task Allocation problem for Swarm Robotic based system. • The proposal is inspired by Particle Swarm Optimization. • We optimize the communication topology using a clustered configuration to reduce both execution time and battery charge usage. • We achieve a significant improvement both in terms of convergence time and battery charge requirement over the approach using a mesh topology. • We demonstrate that the proposed algorithm has real chances to be used in real-word applications based on swarm robotics when compared to existing well-known models. [ABSTRACT FROM AUTHOR]

It is difficult to estimate Lithium-ion battery state of charge (SOC) accurately. By using extended Kalman filter (EKF).the interference of system noise can be effectively reduced, which improved the estimation accuracy. First, the battery model was studied and a Thevenin model was established. Then the appropriate battery charge-and-discharge experiments were performed to identify the parameters of the model. Finally EKF applied to the model experiments show that EKF has high precision. [ABSTRACT FROM AUTHOR]

Lithium iron phosphate battery as the research object, in view of the traditional battery state of charge (SoC) estimate methodological shortcomings and deficiencies, combined with battery charge and discharge characteristics. This paper presents an improved BP neural network algorithm which can significantly reduce the SoC prediction error of the lithium iron phosphate battery. Through a lot of experiments, the improved training function is put forward in this paper. Comparing the SoC value of the lithium battery and the actual SoC value estimated by the neural network, the effectiveness of the algorithm is proved. Research results show that the consumption of the algorithm to the real-time measurement of voltage, current and temperature value and the internal resistance value as input to learn lithium battery power remaining, with estimated speed, wide application range and prediction error is small, the engineering easy to achieve, can effectively solve the prediction problem of the state of charge (SoC) of the lithium batteries for electric vehicles. [ABSTRACT FROM AUTHOR]

In this paper, a frequency control strategy of hybrid energy storage system (HESS) for autonomous microgrid (AMG) based on a frequency hysteretic loop is proposed. The control strategy is composed of two modes. Mode I coordinates the relationship between the frequency control precision and the battery charge/discharge cycles. Mode II coordinates the charge/discharge priorities of battery and supercapacitor to achieve the optimal control of different energy storage systems. Finally, a test system is established to verify the effectiveness of the proposed frequency hysteretic loop based control strategy of HESS. The proposed frequency control strategy can make significant contribution to the stable operation of MG and promote the utilization level of renewable energy resources. [ABSTRACT FROM AUTHOR]

We report the design of a low-temperature liquid metal battery (LMB). Li and Ga as the negative and positive electrode, respectively, are used in combination with a room temperature ionic liquid as an electrolyte. 1 mol/L lithium bis(trifluoromethylsulfonyl)imide (Li[TFSI]) in 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide is chosen as electrolyte. The battery operates at 220°C which is a relatively low temperature for a LMB and shows good electrochemical performance at low current density. The cells were cycled for more than 600 h and achieved a round-trip Coulombic efficiency close to 100% and an average voltage efficiency of 66% resulting in an overall energy efficiency of 65%. At higher current densities, however, the system showed up to 75% irreversible capacity loss after three cycles. To understand the origin of this strong deterioration, we characterized the surface and the bulk properties of the Ga cathode using X-ray Photoelectron Spectroscopy. Especially at higher current densities a decomposition of the electrolyte was found. The chemical changes that occurred and the elemental distribution at the Ga cathode are analyzed based on XPS measurements at different stages of the battery charge/discharge cycling. [ABSTRACT FROM AUTHOR]

The analysis of the aircraft onboard cables design made by the authors has shown that it is most expedient to reduce the weight of the bonding of electrical connectors through replacing a molded housing of the plug connector by a lightweight one, while keeping to the requirements of shielding the cable bonding assembly from radio interference. 0.15÷0.2 mm thick aluminum foil was chosen as a material for the tubular lightweight housing. To obtain lightweight tubular products for space engineering it was suggested to use magnetic impulse welding-forming (MIWF), which applies integrated force and thermal action on the workpiece. We described the physical nature of MIWF process and defined the ranges of energy parameters affecting the quality of welded joints: operating voltage of the battery charge of capacitors, capacity of the equipment storage unit, inductance of the working tool - inductor - characterized by a number of turns. The combination of these parameters determines the energy and the duration of the action to the workpiece. The results of the experimental studies are provided. The industrial technology has been developed. [ABSTRACT FROM AUTHOR]

Recently, "budget" dental light-emitting diode (LED)-based light-curing units (LCUs) have become available over the Internet. These LCUs claim equal features and performance compared to LCUs from major manufacturers, but at a lower cost. This study examined radiant power, spectral emission, beam irradiance profiles, effective emission ratios, and the ability of LCUs to provide sustained output values during the lifetime of a single, fully charged battery. Three examples of each budget LCU were purchased over the Internet (KY-L029A and KY-L036A, Foshan Keyuan Medical Equipment Co, and the Woodpecker LED.B, Guilin Woodpecker Medical Instrument Co). Major dental manufacturers provided three models: Elipar S10 and Paradigm (3M ESPE) and the Bluephase G2 (Ivoclar Vivadent). Radiant power emissions were measured using a laboratory-grade thermopile system, and the spectral emission was captured using a spectroradiometer system. Irradiance profiles at the tip end were measured using a modified laser beam profiler, and the proportion of optical tip area that delivered in excess of 400 mW/cm2 (termed the effective emission ratio) was displayed using calibrated beam profile images. Emitted power was monitored over sequential exposures from each LCU starting at a fully charged battery state. The results indicated that there was less than a 100-mW/ cm2 difference between manufacturer-stated average tip end irradiance and the measured output. All the budget lights had smaller optical tip areas, and two demonstrated lower effective emission ratios than did the units from the major manufacturers. The budget lights showed discontinuous values of irradiance over their tip ends. One unit delivered extremely high output levels near the center of the light tip. Two of the budget lights were unable to maintain sustained and stable light output as the battery charge decreased with use, whereas those lights from the major manufacturers all provided a sustained light output for at least 100 exposures as well as visual and audible indications that the units required recharging. [ABSTRACT FROM AUTHOR]

A wide variety of rapidly evolving algorithms of lithium-ion battery charge leads to the lack of statistics on the differential coefficient of a specific battery degradation, or in other words, a misunderstanding of the difference in the state of charge after several charge-discharge cycles as compared to a single one. As a solution of the problem the authors propose the usage of a universal integrated algorithm of LiFePO4 batteries charging with initial and final trickle charge, which will both train the battery and reduce the differential coefficient of degradation, as well as allow testing of local grid power which the battery is charging from. This approach, if distributed widely, may give rich statistic information to be used for further improvement of charge algorithms. [ABSTRACT FROM AUTHOR]

Coordinated electric-vehicle charging can produce optimal, flattened loads that would improve reliability of the power system as well as reduce system costs and emissions. Optimal deadline scheduling of residential charging would require customers to defer charging their vehicles and to accept less than a 100% target for battery charge. To analyze the necessary incentives for customers to accept giving up control of when charging of their vehicles takes place, we use data from a choice experiment implemented in an online survey of electric-vehicle owners and lessees in upstate New York (N=462). The choice microdata allowed us to make inference on the willingness to pay for features of hypothetical coordinated electric-vehicle charging programs, exploiting Variational Bayes (VB) inference. Our results show that individuals negatively perceive the duration of the timeframe in which the energy provider would be allowed to defer charging. A negative monetary valuation is evidenced by an expected average reduction in the annual fee of joining the coordinated charging program of $2.66 per hour of control yielded to the energy provider. Our results also provide evidence of substantial heterogeneity in preferences, probably due to early-stage attitudes toward coordinated charging. For example, the 25% quantile of the posterior distribution of the mean of the willingness to accept an additional hour of control yielded to the utility is $4.72. However, the negative valuation of the timeframe for deferring charging is compensated by positive valuation of emission savings coming from switching charging to periods of the day with a higher proportion of generation from renewable sources. Customers also positively valued discounts in the price of energy delivery. [ABSTRACT FROM AUTHOR]

This paper deals with the management of Energy Storage System (ESS) connected in a microgrid with a PV array and regulate the battery charge, hold and discharge operations using DC-DC bidirectional converter based on the requirement of the Load. The PV array along with the battery and load is simulated for various conditions such as PV supplying and charging the battery, PV supplying only the load, battery supplying the load and PV-Battery both supplying the load. The output parameters like voltage, current and power graphs are plotted and analysed for each condition. The entire paper is simulated on Matlab-Simulink environment. [ABSTRACT FROM AUTHOR]

A semi-autonomous 4-wheeled robot (TickBot) was fitted with a denim cloth treated with an acaricide (permethrin™) and tested for its ability to control ticks in a tick-infested natural environment in Portsmouth, Virginia. The robot's sensors detect a magnetic field signal from a guide wire encased in 80 m polyethylene tubing, enabling the robot to follow the trails, open areas and other terrain where the tubing was located. To attract ticks to the treated area, CO 2 was distributed through the same tubing, fitted with evenly spaced pores and flow control valves, which permitted uniform CO 2 distribution. Tests were done to determine the optimum frequency for TickBot to traverse the wire-guided treatment site as well as the duration of operation that could be accomplished on a single battery charge. Prior to treatment, dragging was done to determine the natural abundance of ticks in the test site. Controls were done without CO 2 and without permethrin. TickBot proved highly effective in reducing the overall tick densities to nearly zero with the treatment that included both carbon dioxide pretreatment and the permethrin treated cloth. Following a 60 min traverse of the treatment areas, adult tick numbers, almost entirely Amblyomma americanum , was reduced to zero within 1 h and remained at or near zero for 24 h. Treatments without CO 2 also showed reduction of ticks to near zero within 1 h, but the populations were no different than the control sections at 4 h. This study demonstrates the efficacy of TickBot as a tick control device to significantly reduce the risk of tick bites and disease transmission to humans and companion animals visiting a previously tick-infested natural environment. Continued deployment of TickBot for additional days or weeks can assure a relatively tick-safe environment for enjoyment by the public. [ABSTRACT FROM AUTHOR]

This paper presents a design of a bidirectional 4 phase interleave converter specifically for PV applications. The proposed model has rated capacity of 60 to 120 VDC, 1KW. The Design of this DC-DC bidirectional 4 phase interleave converter to investigate the behavior of the system used MATLAB/SIMULINK. The simulation results are observed to determine the output voltage value. The design used FIO controller to decision battery charge or discharge status. The first step is boost converter to transfer power from battery into 120Vdc bus and the second step is working as buck converter to store energy into the battery 60Vdc when no load required. Mathematical models for boost and buck modes are being derived and the Simulink model is constructed in order to simulate the system of both step designs. The results of simulation found that the designed converter is able to charge battery and discharge battery and deliver power to load as designed. The output current is 12A (2.3A per phase) battery capacity of selected Lead-Acid battery per designed is 12Ah. [ABSTRACT FROM AUTHOR]

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This paper focuses on the performance of traction lithium-ion batteries. The kinetic process of battery electrode system was analyzed by fitting the measured electrochemical impedance curve with equivalent circuit. The parameters of equivalent circuit model in different SOC ranges were selected to analyze the different AC impedance components and the influence on battery charging and discharging characteristics. The results show that the parameters of equivalent circuit model obtained with impedance spectra test can get battery charge transfer impedance and diffusion impedance in higher accuracy respectively. The distinction between electrochemical polarization and concentration polarization is helpful to analyze the battery charging and discharging performance in different temperatures and SOC. [ABSTRACT FROM AUTHOR]

Abstract: Context: Worldwide mobile device sales will reach 821 Million units in 2012 and will rise to 1.2 Billion in 2013 [1]. Inevitably the paradigm for access information and Internet services is increasingly migrating to mobile. Context-aware services can help to improve the user experience because they can adapt themselves to the users’ context but, despite the improvements in terms of hardware, the the main obstacle towards a widespread adoption of such services is the limited battery life. A context-aware service requires the installation of a Context-Broker Application, which generates a continuous flow of data from the smartphone and a constant usage of its equipped sensors: as a consequence the considerable increase of energy consumption becomes a problem. Aim: The aim of this work is to propose gLCB an Energy Efficient Context-Aware middleware for Android OS, which is able to collect Context Information and to send it to a remote platform in an energy-efficient way. The gLCB application proposes a new energy-aware data collection based on user profiles. Methods: We define policies based on battery consumption profiles, which are selected depending on modifications of the context information. Moreover, we have implemented an automatic consumption testing mechanism and a statistical treatment of results to provide a reliable validation of gLCB in terms of energy efficiency. Results: Experimental results show that our middleware got the best trade-off between number of server uploads and battery lifetime with the policies computed automatically by the device. This means that the way in which software is written can impact the energy consumption of a mobile device and service adaptation can be based on the actual value of the battery charge. [Copyright &y& Elsevier]

Abstract: Wireless sensor networks comprise an important research area and a near future for industry and communications. Wireless sensor networks contain resource-constrained sensor nodes that are powered by small batteries, limited process and memory and wireless communication. These features give sensors their versatility and drawbacks, such as their limited operating lifetimes. To feasibly deploy wireless sensor networks with isolated motes, several approaches and solutions have been developed; the most common, apart from using alternative power sources such as solar panels, are those that put sensors to sleep for time periods established by the application. We thus propose a fuzzy rule-based system that estimates the next duty cycle, taking the magnitude being tested and battery charge as input. To show how it works, we compare an analytical delta system to our contribution. As an application to test both systems, a sound pressure monitoring application is presented. The results have shown that the fuzzy rule-based system better predicts the evolution of the magnitude by which errors committed by idle periods decrease. This work also shows that application-oriented duty cycle control can be an alternative for measuring systems, thus saving battery and improving sensor node lifetime, with a reasonable loss of precision. [Copyright &y& Elsevier]

We analyse energy efficiency versus quality characteristics of hashing algorithms in a mobile device and describe methodologies for energy measurement on a Javaenabled smart phone. Energy efficiency of 17 hash functions (Adler32, Crc16, Crc32, Haval256, MD2, MD4, MD5, MD6, SHA1, SHA224, SHA256, SHA384, SHA512, Skein, SV1, Tiger, Whirlpool) is evaluated using the GSM modem-based battery charge measurement method, and quality is evaluated using the Avalanche and Chi-square tests. The results show that the most energy-efficient hash function on a mobile device is SV1 for cryptographic applications, and crc16 for noncryptographic applications. [ABSTRACT FROM AUTHOR]

Current lithium-oxygen (Li-O 2) batteries suffer from large charge overpotentials related to electronic resistivity of the insulating lithium peroxide (Li 2 O 2) discharge product. One potential solution to this challenge is the stabilization of the lithium superoxide (LiO 2) discharge intermediate, which has much higher electronic conductivity compared to Li 2 O 2. Cathodes based on small iridium (Ir) nanoparticles have been recently used in a Li-O 2 battery to successfully stabilize the LiO 2 product, however, the LiO 2 had a short lifetime. In the previous study, researchers found that the LiO 2 was stabilized on Ir 3 Li surfaces which were formed from Ir nanoparticles during battery operation. Little is known about the electronic properties of Ir 3 Li and its role in stabilizing LiO 2 product formation. This work provides the first study of the electronic properties of Ir 3 Li, which was thermally synthesized in bulk prior to implementation on the reduced graphene oxide (rGO) cathode of a Li-O 2 cell. The bulk Ir 3 Li was found to have comparable electrical conductivity to Ir metal, possess metal-like magnetic properties, and has an affinity towards O 2 adsorption. The LiO 2 discharge product formed from the Li-O 2 battery discharge was characterized using Raman spectroscopy, titration, along with a comprehensive transmission electron microscopy (TEM) study. This analysis revealed the formation of ultra-nanocrystalline LiO 2 particles greater than 200 nm. This result was attributed to the use of large micron sized Ir 3 Li particles, which could stabilize larger LiO 2 particles compared to previous cathodes that utilized Ir nanoparticles that partially converted to Ir 3 Li during cycling. These results demonstrate that cathode properties can be modified to stabilize the bulk LiO 2 discharge product, which can be useful for the further development of LiO 2 -based Li-O 2 batteries. [Display omitted] • Bulk synthesis and characterization of Ir 3 Li as Li-O2 battery cathode material. • Reduced Li-O 2 battery charge overpotentials using Ir 3 Li-rGO cathodes. • Formation of stable, > 200 nm particles of lithium superoxide as discharge product. [ABSTRACT FROM AUTHOR]

The article presents information about some latest pharmaceutical products. Matrix Technologies introduces Cellmate II, a cordless serologics pipettor for use with graduated and volumentric glass and plastic serological pipettes. Large aspirate and dispense triggers allow precise control of liquid manipulations, and a LCD display monitors battery charge and pump speeds for both aspiration and dispense. Collaboration between Microfluidics and Absolute Control Systems Inc. has yielded a design for a containment isolator for the Microfluidizer fluid processor, a unit that uses pressures up to 40,000 pounds per square inch to process stable, immiscible liquid emulsions and solids in liquid suspensions.

The aim of this paper is to propose a power control strategy for hybrid electrical vehicles. This strategy uses a fuel consumption criterion with battery charge sustaining. It is based on an instantaneous minimization of the equivalent fuel flow. Two comparisons are performed to evaluate the proposed strategy. The first one uses the loss minimization strategy of Seiler and Schröder [1], which appears to be realistic and efficient for real-time control. This strategy is also based on an instantaneous optimization and allows the battery state of charge to be taken into account. The second comparison is made with an optimal solution found for a given driving schedule. Although not realistic for real-time control, this solution is derived through a global optimization algorithm, the well-known simulated annealing method. [ABSTRACT FROM AUTHOR]

Background: Google Glass is a promising premarket device that includes an optical head-mounted display. Several proof of concept reports exist, but there is little scientific evidence regarding its use in a medical setting.Objective: The objective of this study was to empirically determine the feasibility of deploying Glass in a forensics setting.Methods: Glass was used in combination with a self-developed app that allowed for hands-free operation during autopsy and postmortem examinations of 4 decedents performed by 2 physicians. A digital single-lens reflex (DSLR) camera was used for image comparison. In addition, 6 forensic examiners (3 male, 3 female; age range 23-48 years, age mean 32.8 years, SD 9.6; mean work experience 6.2 years, SD 8.5) were asked to evaluate 159 images for image quality on a 5-point Likert scale, specifically color discrimination, brightness, sharpness, and their satisfaction with the acquired region of interest. Statistical evaluations were performed to determine how Glass compares with conventionally acquired digital images.Results: All images received good (median 4) and very good ratings (median 5) for all 4 categories. Autopsy images taken by Glass (n=32) received significantly lower ratings than those acquired by DSLR camera (n=17) (region of interest: z=-5.154, P<.001; sharpness: z=-7.898, P<.001; color: z=-4.407, P<.001, brightness: z=-3.187, P=.001). For 110 images of postmortem examinations (Glass: n=54, DSLR camera: n=56), ratings for region of interest (z=-8.390, P<.001) and brightness (z=-540, P=.007) were significantly lower. For interrater reliability, intraclass correlation (ICC) values were good for autopsy (ICC=.723, 95% CI .667-.771, P<.001) and postmortem examination (ICC=.758, 95% CI .727-.787, P<.001). Postmortem examinations performed using Glass took 42.6 seconds longer than those done with the DSLR camera (z=-2.100, P=.04 using Wilcoxon signed rank test). The battery charge of Glass quickly decreased; an average 5.5% (SD 1.85) of its battery capacity was spent per postmortem examination (0.81% per minute or 0.79% per picture).Conclusions: Glass was efficient for acquiring images for documentation in forensic medicine, but the image quality was inferior compared to a DSLR camera. Images taken with Glass received significantly lower ratings for all 4 categories in an autopsy setting and for region of interest and brightness in postmortem examination. The effort necessary for achieving the objectives was higher when using the device compared to the DSLR camera thus extending the postmortem examination duration. Its relative high power consumption and low battery capacity is also a disadvantage. At the current stage of development, Glass may be an adequate tool for education. For deployment in clinical care, issues such as hygiene, data protection, and privacy need to be addressed and are currently limiting chances for professional use. [ABSTRACT FROM AUTHOR]

Presents a summary of the article `Electric Vehicle Purchasing Intentions: The Concern Over Battery Charge Duration,' by Emmanuel Cheron and Michel Zins, adapted from the May 1997 edition of `Transportation Research, Part A: Policy and Practice.'