164 resultados para Secondary batteries


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One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

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We investigate a collision-sensitive secondary network that intends to opportunistically aggregate and utilize spectrum of a primary network to achieve higher data rates. In opportunistic spectrum access with imperfect sensing of idle primary spectrum, secondary transmission can collide with primary transmission. When the secondary network aggregates more channels in the presence of the imperfect sensing, collisions could occur more often, limiting the performance obtained by spectrum aggregation. In this context, we aim to address a fundamental query, that is, how much spectrum aggregation is worthy with imperfect sensing. For collision occurrence, we focus on two different types of collision: one is imposed by asynchronous transmission; and the other by imperfect spectrum sensing. The collision probability expression has been derived in closed-form with various secondary network parameters: primary traffic load, secondary user transmission parameters, spectrum sensing errors, and the number of aggregated sub-channels. In addition, the impact of spectrum aggregation on data rate is analysed under the constraint of collision probability. Then, we solve an optimal spectrum aggregation problem and propose the dynamic spectrum aggregation approach to increase the data rate subject to practical collision constraints. Our simulation results show clearly that the proposed approach outperforms the benchmark that passively aggregates sub-channels with lack of collision awareness.

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Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

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Background: Ischaemic heart disease (IHD) is the most common cause of death worldwide.

Aim: To determine the long-term impact of organisational interventions for secondary prevention of IHD.

Design and setting: Systematic review and meta-analysis of studies from CENTRAL, MEDLINE®, Embase, and CINAHL published January 2007 to January 2013.

Method: Searches were conducted for randomised controlled trials of patients with established IHD, with long-term follow-up, of cardiac secondary prevention programmes targeting organisational change in primary care or community settings. A random-effects model was used and risk ratios were calculated.

Results: Five studies were included with 4005 participants. Meta-analysis of four studies with mortality data at 4.7–6 years showed that organisational interventions were associated with approximately 20% reduced mortality, with a risk ratio (RR) for all-cause mortality of 0.79 (95% confidence interval [CI] = 0.66 to 0.93), and a RR for cardiac-related mortality of 0.74 (95% CI = 0.58 to 0.94). Two studies reported mortality data at 10 years. Analysis of these data showed no significant differences between groups. There were insufficient data to conduct a meta-analysis on the effect of interventions on hospital admissions. Additional analyses showed no significant association between organisational interventions and risk factor management or appropriate prescribing at 4.7–6 years.

Conclusion: Cardiac secondary prevention programmes targeting organisational change are associated with a reduced risk of death for at least 4–6 years. There is insufficient evidence to conclude whether this beneficial effect is maintained indefinitely.

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The worldwide scarcity of women studying or employed in ICT, or in computing related disciplines, continues to be a topic of concern for industry, the education sector and governments. Within Europe while females make up 46% of the workforce only 17% of IT staff are female. A similar gender divide trend is repeated worldwide, with top technology employers in Silicon Valley, including Facebook, Google, Twitter and Apple reporting that only 30% of the workforce is female (Larson 2014). Previous research into this gender divide suggests that young women in Secondary Education display a more negative attitude towards computing than their male counterparts. It would appear that the negative female perception of computing has led to representatively low numbers of women studying ICT at a tertiary level and consequently an under representation of females within the ICT industry. The aim of this study is to 1) establish a baseline understanding of the attitudes and perceptions of Secondary Education pupils in regard to computing and 2) statistically establish if young females in Secondary Education really do have a more negative attitude towards computing.

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The objective of this study was to evaluate the impact of restricting high-risk antibiotics on methicillin-resistant Staphylococcus aureus (MRSA) incidence rates in a hospital setting. A secondary objective was to assess the impact of reducing fluoroquinolone use in the primary-care setting on MRSA incidence in the community. This was an interventional, retrospective, ecological investigation in both hospital and community (January 2006 to June 2010). Segmented regression analysis of interrupted time-series was employed to evaluate the intervention. The restriction of high-risk antibiotics was associated with a significant change in hospital MRSA incidence trend (coefficient=-0·00561, P=0·0057). Analysis showed that the intervention relating to reducing fluoroquinolone use in the community was associated with a significant trend change in MRSA incidence in community (coefficient=-0·00004, P=0·0299). The reduction in high-risk antibiotic use and fluoroquinolone use contributed to both a reduction in incidence rates of MRSA in hospital and community (primary-care) settings. 

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The invention provides ionic liqs., [R'1CH(OH)CH2]NR'nX (X = anion, R' = alkyl, alkenyl, alkynyl, cycloalkyl, alkylcarbonylalkyl, alkoxy, haloalkyl, haloalkoxy, alkenyloxy, alkynyloxy, cycloalkyloxy, aryl), having a secondary hydroxyl group, and an atom-efficient method for the prepn. of these ionic liqs., by epoxidn. of a protonated nitrogen- contg. org. base (which can optionally be prepd. in situ) in the presence of an anion suitable for supporting ionic liq. formation. Thus, reaction of 1-methylimidazole with HCl in EtOH ∼ 25° followed by treatment with propylene oxide gave 1-(2-hydroxypropyl)-3-methylimidazolium chloride. [on SciFinder(R)]

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Three-dimensional ordered mesoporous (3DOM) ZnCo2O4 materials have been synthesized via a hard template and used as bifunctional electrocatalysts for rechargeable Li-O2 batteries. The as-prepared ZnCo2O4 nanoparticles possess a high specific surface area of 127.2 m2 g-1 and a spinel crystalline structure. The Li-O2 battery utilizing 3DOM ZnCo2O4 shows a higher specific capacity of 6024 mAh g-1 than that with pure Ketjen black (KB). Moreover, the ZnCo2O4-based electrode enables much enhanced cyclability with a smaller discharge-recharge voltage gap than that of the carbon-only cathode. Such excellent catalytic performance of ZnCo2O4 could be associated with its larger surface area and 3D ordered mesoporous structure

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Li-rich materials are considered the most promising for Li-ion battery cathodes, as high capacity can be achieved. However, poor cycling stability is a critical drawback that leads to poor capacity retention. Here a strategy is used to synthesize a large-grain lithium-rich layered oxides to overcome this difficulty without sacrificing rate capability. This material is designed with micron scale grain with a width of about 300 nm and length of 1-3 μm. This unique structure has a better ability to overcome stress-induced structural collapse caused by Li-ion insertion/extraction and reduce the dissolution of Mn ions, which enable a reversible and stable capacity. As a result, this cathode material delivered a highest discharge capacity of around 308 mAh g-1 at a current density of 30 mA g-1 with retention of 88.3% (according to the highest discharge capacity) after 100 cycles, 190 mAh g-1 at a current density of 300 mA g-1 and almost no capacity fading after 100 cycles. Therefore, Lithium-rich material of large-grain structure is a promising cathode candidate in Lithium-ion batteries with high capacity and high cycle stability for application. This strategy of large grain may furthermore open the door to synthesize the other complex architectures for various applications.

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The electrochemical performance of one-dimensional porous La0.5Sr0.5CoO2.91 nanotubes as a cathode catalyst for rechargeable nonaqueous lithium-oxygen (Li-O2) batteries is reported here for the first time. In this study, one-dimensional porous La0.5Sr0.5CoO2.91 nanotubes were prepared by a simple and efficient electrospinning technique. These materials displayed an initial discharge capacity of 7205 mAh g-1 with a plateau at around 2.66 V at a current density of 100 mA g-1. It was found that the La0.5Sr0.5CoO2.91 nanotubes promoted both oxygen reduction and oxygen evolution reactions in alkaline media and a nonaqueous electrolyte, thereby improving the energy and coulombic efficiency of the Li-O2 batteries. The cyclability was maintained for 85 cycles without any sharp decay under a limited discharge depth of 1000 mAh g-1, suggesting that such a bifunctional electrocatalyst is a promising candidate for the oxygen electrode in Li-O2 batteries.

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We describe a novel strategy for in situ fabrication of hierarchical Fe3O4 nanoclusters-GAs. Fe3O4 NCs-GAs deliver excellent rate capability (the reversible capacities obtained were 1442, 392 and 118 mA h g-1 at 0.1C, 12C and 35C rates), and a high reversible capacity of 577 mA h g-1 over 300 cycles at the current density of 5.2 A g-1 (6C).

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A three-dimensional (3D) graphene-Co3O4 electrode was prepared by a two-step method in which graphene was initially deposited on a Ni foam with Co3O4 then grown on the resulting graphene structure. Cross-linked Co3O4 nanosheets with an open pore structure were fully and vertically distributed throughout the graphene skeleton. The free-standing and binder-free monolithic electrode was used directly as a cathode in a Li-O2 battery. This composite structure exhibited enhanced performance with a specific capacity of 2453 mA h g-1 at 0.1 mA cm-2 and 62 stable cycles with 583 mA h g-1 (1000 mA h gcarbon-1). The excellent electrochemical performance is associated with the unique architecture and superior catalytic activity of the 3D electrode. 

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In this work, an economical route based on hydrothermal and layer-by-layer (LBL) self-assembly processes has been developed to synthesize unique Al 2O3-modified LiV3O8 nanosheets, comprising a core of LiV3O8 nanosheets and a thin Al 2O3 nanolayer. The thickness of the Al2O 3 nanolayer can be tuned by altering the LBL cycles. When evaluated for their lithium-storage properties, the 1 LBL Al2O 3-modified LiV3O8 nanosheets exhibit a high discharge capacity of 191 mA h g-1 at 300 mA g-1 (1C) over 200 cycles and excellent rate capability, demonstrating that enhanced physical and/or chemical properties can be achieved through proper surface modification. © 2014 Elsevier B.V. All rights reserved.

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We describe a simple strategy, which is based on the idea of space confinement, for the synthesis of carbon coating on LiFePO4 nanoparticles/graphene nanosheets composites in a water-in-oil emulsion system. The prepared composite displayed high performance as a cathode material for lithium-ion battery, such as high reversible lithium storage capacity (158 mA h g-1 after 100 cycles), high coulombic efficiency (over 97%), excellent cycling stability and high rate capability (as high as 83 mA h g -1 at 60 C). Very significantly, the preparation method employed can be easily adapted and be extended as a general approach to sophisticated compositions and structures for the preparation of highly dispersed nanosized structure on graphene. 

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A facile method to synthesize well-dispersed TiO2 quantum dots on graphene nanosheets (TiO2-QDs/GNs) in a water-in-oil (W/O) emulsion system is reported. The TiO2/graphene composites display high performance as an anode material for lithium-ion batteries (LIBs), such as having high reversible lithium storage capacity, high Coulombic efficiency, excellent cycling stability, and high rate capability. The excellent electrochemical performance and special structure of the composites thus offer a way to prepare novel graphene-based electrode materials for high-energy-density and high-power LIBs.