On the Performances of Ionic Liquid-Based Electrolytes for Li-NMC Batteries

Herein, the N-butyl-N-methylpyrrolidinium bis(fluorosulfonyl)amide and the N-propyl-N-methylpyrrolidinium bis(fluorosulfonyl)amide room temperature ionic liquids, combined with the lithium bis(trifluoromethanesulfonyl)amide salt, are investigated as electrolytes for Li/LiNi1/3Mn1/3Co1/3O2 (Li/NMC) batteries. To conduct this study, volumetric properties, ionic conductivity and viscosity of the pure ionic liquids and selected electrolytes were firstly determined as a function of temperature and composition in solution. These data were then compared with those measured in the case of the standard alkyl carbonate-based electrolyte: e.g. the EC/PC/3DMC + 1 mol·L−1 LiPF6. The compatibility of the selected electrolytes with the lithium electrode was then investigated by following the evolution of Li/electrolyte interfaces through impedance measurements. Interestingly, the impedances of the investigated Li/electrolyte interfaces were found to be more than three times lower than that measured using the standard electrolyte. Finally, electrochemical performances of the ionic liquid-based electrolytes were investigated using galvanostatic charge and discharge and cyclic voltammetry of each Li/NMC cell. Using these electrolytes, each tested Li cell reaches up to 145 mA·h·g−1 at C/10 and 110 mA·h·g−1 at C with a coulombic efficiency close to 100 %.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

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.

An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

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.

Quasi-periodic stacks of semiconductor layers: Combinatorial frequency generation

The nonlinear scattering and combinatorial frequency generation by the quasi-periodic Fibonacci and Thue-Morse stacks of semiconductor layers have been investigated taking into account the nonlinear charge dynamics. It has been shown that the mixing processes in passive semiconductor structures are driven by the competitive effects of the collision of charges and resonance interactions of carriers with pump waves. The effects of the stack arrangements and constituent layer parameters on the efficiency of the combinatorial frequency generation are discussed. 

An effective three-dimensional ordered mesoporous ZnCo2O4 as electrocatalyst for Li-O2 batteries

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

A design strategy of large grain lithium-rich layered oxides for lithium-ion batteries cathode

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.

One-dimensional porous La0.5Sr0.5CoO2.91 nanotubes as a highly efficient electrocatalyst for rechargeable lithium-oxygen batteries

The electrochemical performance of one-dimensional porous La_0.5Sr_0.5CoO_2.91 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 La_0.5Sr_0.5CoO_2.91 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 La_0.5Sr_0.5CoO_2.91 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.

Three-dimensional graphene-Co3O4 cathodes for rechargeable Li-O2 batteries

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 g_carbon^-1). The excellent electrochemical performance is associated with the unique architecture and superior catalytic activity of the 3D electrode. 

Surface modification of LiV3O8 nanosheets via layer-by-layer self-assembly for high-performance rechargeable lithium batteries

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.

Facile synthesis of nanocrystalline LiFePO4/graphene composite as cathode material for high power lithium ion batteries

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. 

Facile Synthesis of Anatase TiO2 Quantum-Dot/Graphene-Nanosheet Composites with Enhanced Electrochemical Performance for Lithium-Ion Batteries

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. 

In situ synthesis of LiV3O8 nanorods on graphene as high rate-performance cathode materials for rechargeable lithium batteries

We developed a facile two-step hydrothermal procedure to prepare hybrid materials of LiV₃O₈ nanorods on graphene sheets. The special structure endows them with the high-rate transportation of electrolyte ions and electrons throughout the electrode matrix, resulting in remarkable electrochemical performance when they were used as cathodes in rechargeable lithium batteries. © 2013 The Royal Society of Chemistry.

An in situ ionic-liquid-assisted synthetic approach to iron fluoride/graphene hybrid nanostructures as superior cathode materials for lithium ion batteries

A tactful ionic-liquid (IL)-assisted approach to in situ synthesis of iron fluoride/graphene nanosheet (GNS) hybrid nanostructures is developed. To ensure uniform dispersion and tight anchoring of the iron fluoride on graphene, we employ an IL which serves not only as a green fluoride source for the crystallization of iron fluoride nanoparticles but also as a dispersant of GNSs. Owing to the electron transfer highways created between the nanoparticles and the GNSs, the iron fluoride/GNS hybrid cathodes exhibit a remarkable improvement in both capacity and rate performance (230 mAh g^-1 at 0.1 C and 74 mAh g^-1 at 40 C). The stable adhesion of iron fluoride nanoparticles on GNSs also introduces a significant improvement in long-term cyclic performance (115 mAh g^-1 after 250 cycles even at 10 C). The superior electrochemical performance of these iron fluoride/GNS hybrids as lithium ion battery cathodes is ascribed to the robust structure of the hybrid and the synergies between iron fluoride nanoparticles and graphene. © 2013 American Chemical Society.

Inter layer and cooperative design strategies for green mobile networks

The promise of a truly mobile experience is to have the freedom to roam around anywhere and not be bound to a single location. However, the energy required to keep mobile devices connected to the network over extended periods of time quickly dissipates. In fact, energy is a critical resource in the design of wireless networks since wireless devices are usually powered by batteries. Furthermore, multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the bene ts gained from multiple interfaces come at a cost in terms of energy consumption having profound e ect on the mobile battery lifetime and standby time. This concern is rea rmed by the fact that battery lifetime is one of the top reasons why consumers are deterred from using advanced multimedia services on their mobile on a frequent basis. In order to secure market penetration for next generation services energy e ciency needs to be placed at the forefront of system design. However, despite recent e orts, energy compliant features in legacy technologies are still in its infancy, and new disruptive architectures coupled with interdisciplinary design approaches are required in order to not only promote the energy gain within a single protocol layer, but to enhance the energy gain from a holistic perspective. A promising approach is cooperative smart systems, that in addition to exploiting context information, are entities that are able to form a coalition and cooperate in order to achieve a common goal. Migrating from this baseline, this thesis investigates how these technology paradigm can be applied towards reducing the energy consumption in mobile networks. In addition, we introduce an additional energy saving dimension by adopting an interlayer design so that protocol layers are designed to work in synergy with the host system, rather than independently, for harnessing energy. In this work, we exploit context information, cooperation and inter-layer design for developing new energy e cient and technology agnostic building blocks for mobile networks. These technology enablers include energy e cient node discovery and short-range cooperation for energy saving in mobile handsets, complemented by energy-aware smart scheduling for promoting energy saving on the network side. Analytical and simulations results were obtained, and veri ed in the lab on a real hardware testbed. Results have shown that up to 50% energy saving could be obtained.

Design and evaluation of multi-band RF energy harvesting circuits and antennas for WSNs

Radio frequency (RF) energy harvesting is an emerging technology that will enable to drive the next generation of wireless sensor networks (WSNs) without the need of using batteries. In this paper, we present RF energy harvesting circuits specifically developed for GSM bands (900/1800) and a wearable dual-band antenna suitable for possible implementation within clothes for body worn applications. Besides, we address the development and experimental characterization of three different prototypes of a five-stage Dickson voltage multiplier (with match impedance circuit) responsible for harvesting the RF energy. Different printed circuit board (PCB) fabrication techniques to produce the prototypes result in different values of conversion efficiency. Therefore, we conclude that if the PCB fabrication is achieved by means of a rigorous control in the photo-positive method and chemical bath procedure applied to the PCB it allows for attaining better values for the conversion efficiency. All three prototypes (1, 2 and 3) can power supply the IRIS sensor node for RF received powers of -4 dBm, -6 dBm and -5 dBm, and conversion efficiencies of 20, 32 and 26%, respectively. © 2014 IEEE.