837 resultados para Vehicular batteries
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In electric vehicles, passengers sit very close to an electric system of significant power. The high currents achieved in these vehicles mean that the passengers could be exposed to significant magnetic fields. One of the electric devices present in the power train are the batteries. In this paper, a methodology to evaluate the magnetic field created by these batteries is presented. First, the magnetic field generated by a single battery is analyzed using finite elements simulations. Results are compared to laboratory measurements, taken from a real battery, in order to validate the model. After this, the magnetic field created by a complete battery pack is estimated and results are discussed.
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The production of electronic equipment, such as computers and cell phones, and, consequently, batteries, has increased dramatically. One of the types of batteries whose production and consumption has increased in recent times is the nickel metal hydride (NiMH) battery. This study evaluated a hydrometallurgical method of recovery of rare earths and a simple method to obtain a solution rich in Ni-Co from spent NiMH batteries. The active materials from both electrodes were manually removed from the accumulators and leached. Several acid and basic solutions for the recovery of rare earths were evaluated. Results showed that more than 98 wt.% of the rare earths were recovered as sulfate salts by dissolution with sulfuric acid, followed by selective precipitation at pH 1.2 using sodium hydroxide. The complete process. precipitation at pH 1.2 followed by precipitation at pH 7, removed about 100 wt.% of iron and 70 wt.% of zinc from the leaching solution. Results were similar to those found in studies that used solvent extraction. This method is easy, economic, and does not pose environmental threats of solvent extraction. (C) 2009 Elsevier B.V. All rights reserved.
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The purpose of this paper is to study metal separation from a sample composed of a mixture of the main types of spent household batteries, using a hydrometallurgical route, comparing selective precipitation and liquid-liquid extraction separation techniques. The preparation of the solution consisted of: grinding the waste of mixed batteries, reduction and volatile metals elimination using electric furnace and acid leaching. From this solution two different routes were studied: selective precipitation with sodium hydroxide and liquid-liquid extraction using Cyanex 272 [bis(2,4,4-trimethylpentyl) phosphoric acid] as extracting agent. The best results were obtained from liquid-liquid extraction in which Zn had a 99% extraction rate at pH 2.5. More than 95% Fe was extracted at pH 7.0, the same pH at which more than 90% Ce was extracted. About 88% Mn, Cr and Co was extracted at this pH. At pH 3.0, more than 85% Ni was extracted, and at pH 3.5 more than 80% of Cd and La was extracted. (C) 2010 Elsevier Ltd. All rights reserved.
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Considering vehicular transport as one of the most health‐relevant emission sources of urban air, and with aim to further understand its negative impact on human health, the objective of this work was to study its influence on levels of particulate‐bound PAHs and to evaluate associated health risks. The 16 PAHs considered by USEPA as priority pollutants, and dibenzo[a, l]pyrene associated with fine (PM2.5) and coarse (PM2.5–10) particles were determined. The samples were collected at one urban site, as well as at a reference place for comparison. The results showed that the air of the urban site was more seriously polluted than at the reference one, with total concentrations of 17 PAHs being 2240% and 640% higher for PM2.5 and PM2.5–10, respectively; vehicular traffic was the major emission source at the urban site. PAHs were predominantly associated with PM2.5 (83% to 94% of ΣPAHs at urban and reference site, respectively) with 5 rings PAHs being the most abundant groups of compounds at both sites. The risks associated with exposure to particulate PAHs were evaluated using the TEF approach. The estimated value of lifetime lung cancer risks exceeded the health‐based guideline levels, thus demonstrating that exposure to PM2.5‐bound PAHs at levels found at urban site might cause potential health risks. Furthermore, the results showed that evaluation of benzo[a] pyrene (regarded as a marker of the genotoxic and carcinogenic PAHs) alone would probably underestimate the carcinogenic potential of the studied PAH mixtures.
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In the last decade, both scientific community and automotive industry enabled communications among vehicles in different kinds of scenarios proposing different vehicular architectures. Vehicular delay-tolerant networks (VDTNs) were proposed as a solution to overcome some of the issues found in other vehicular architectures, namely, in dispersed regions and emergency scenarios. Most of these issues arise from the unique characteristics of vehicular networks. Contrary to delay-tolerant networks (DTNs), VDTNs place the bundle layer under the network layer in order to simplify the layered architecture and enable communications in sparse regions characterized by long propagation delays, high error rates, and short contact durations. However, such characteristics turn contacts very important in order to exchange as much information as possible between nodes at every contact opportunity. One way to accomplish this goal is to enforce cooperation between network nodes. To promote cooperation among nodes, it is important that nodes share their own resources to deliver messages from others. This can be a very difficult task, if selfish nodes affect the performance of cooperative nodes. This paper studies the performance of a cooperative reputation system that detects, identify, and avoid communications with selfish nodes. Two scenarios were considered across all the experiments enforcing three different routing protocols (First Contact, Spray and Wait, and GeoSpray). For both scenarios, it was shown that reputation mechanisms that punish aggressively selfish nodes contribute to increase the overall network performance.
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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.
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Fundação para a Ciência e a Tecnologia (FCT-MCTES) under the grant SFRH/BD/69306/2010
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Scarcity of fuels, changes in environmental policy and in society increased the interest in generating electric energy from renewable energy sources (RES) for a sustainable energy supply in the future. The main problem of RES as solar and wind energy, which represent a main pillar of this transition, is that they cannot supply constant power output. This results inter alia in an increased demand of backup technologies as batteries to assure electricity system safety. The diffusion of energy storage technologies is highly dependent on the energy system and transport transition pathways which might lead to a replacement or reconfiguration of embedded socio-technical practices and regimes (by creating new standards or dominant designs, changing regulations, infrastructure and user patterns). The success of this technology is dependent on hardly predictable future technical advances, actor preferences, development of competing technologies and designs, diverging interests of actors, future cost efficiencies, environmental performance, the evolution of market demand and design and evolution of our society.
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This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.
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Studies in Computational Intelligence, 616
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There is an increasing interest in thin and flexible energy storage devices to meet modern society needs for applications such as, radio frequency sensing, interactive packaging and other consumer products. Printed batteries comply these requirements and are an excellent alternative to conventional batteries for many applications. Flexible and micro-batteries are also included in the area of printed batteries whenever fabricated by printing technologies. The main characteristics, advantages, disadvantages, developments, and printing techniques of printed batteries are presented and discussed in this review. The state-of-art takes into account both the research and industrial levels. In the academic one, the research progress of printed batteries is summarized divided in lithium-ion battery (Li-ion), zinc-manganese dioxide (Zn-MnO2), and other battery types with emphasis on the different materials for anode, cathode and separator as well as in the battery design. With respect to the industrial state-of-art, materials, device formulations and manufacturing techniques are presented. Finally, the prospects and challenges of printed batteries are discussed.
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This review deals with the recent developments and present status of the theoretical models for the simulation of the performance of lithium ion batteries. Preceded by a description of the main materials used for each of the components of a battery -anode, cathode and separator- and how material characteristics affect battery performance, a description of the main theoretical models describing the operation and performance of a battery are presented. The influence of the most relevant parameters of the models, such as boundary conditions, geometry and material characteristics are discussed. Finally, suggestions for future work are proposed.
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This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.