Real-space mapping of dynamic phenomena during hysteresis loop measurements: Dynamic switching spectroscopy piezoresponse force microscopy

Dynamic switching spectroscopy piezoresponse force microscopy is developed to separate thermodynamic and kinetic effects in local bias-induced phase transitions. The approaches for visualization and analysis of five-dimensional data are discussed. The spatial and voltage variability of relaxation behavior of the a-c domain lead zirconate-titanate surface suggest the interpretation in terms of surface charge dynamics. This approach is applicable to local studies of dynamic behavior in any system with reversible bias-induced phase transitions ranging from ferroelectrics and multiferroics to ionic systems such as batteries, fuel cells, and electroresistive materials. (C) 2011 American Institute of Physics. [doi:10.1063/1.3590919]

The partially reversible formation of Li-metal particles on a solid Li electrolyte:applications toward nanobatteries

The feasibility of large-scale implementation of Li-air batteries (LABs) hinges on understanding the thermodynamic and kinetic factors that control charge-discharge rates, efficiency and life times. Here, the kinetics of bias-induced reactions is explored locally on the surface of Li-ion conductive glass ceramics, a preferred electrolyte for LABs, using direct current-voltage and strain spectroscopies. Above a critical bias, particle growth kinetics were found to be linear in both the bias and time domains. Partial reversibility was observed for Li particles as evidenced by the presence of anodic peaks following the Li(+) reduction, as well an associated reduction in particle height. The degree of reversibility was highest for the smallest particles formed. These observations thus suggest the possibility of producing nanobatteries with an active anode volume of the order of 0.1 al.

Viscosity and Carbon Dioxide Solubility for LiPF6, LiTFSI, and LiFAP in Alkyl Carbonates: Lithium Salt Nature and Concentration Effect

Improving fuel economy application of the organic Rankine Cycle on a hybrid bus

Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Sandwich nanoarchitecture of LiV3O8/graphene multilayer nanomembranes via layer-by-layer self-assembly for long-cycle-life lithium-ion battery cathodes

A lack of suitable high-performance cathode materials has become the major barrier to their applications in future advanced communication equipment and electric vehicle power systems. In this paper, we have developed a layer-by-layer self-assembly approach for fabricating a novel sandwich nanoarchitecture of multilayered LiV₃O₈ nanoparticle/graphene nanosheet (M-nLVO/GN) hybrid electrodes for potential use in high performance lithium ion batteries by using a porous Ni foam as a substrate. The prepared sandwich nanoarchitecture of M-nLVO/GN hybrid electrodes exhibited high performance as a cathode material for lithium-ion batteries, such as high reversible specific capacity (235 mA h g^-1 at a current density of 0.3 A g^-1), high coulombic efficiency (over 98%), fast rate capability (up to a current density of 10 A g^-1), and superior capacity retention during cycling (90% capacity retention with a current density of 0.3 A g^-1 after 300 cycles). Very significantly, this novel insight into the design and synthesis of sandwich nanoarchitecture would extend their application to various electrochemical energy storage devices, such as fuel cells and supercapacitors.

2D Monolayer MoS2–Carbon Interoverlapped Superstructure: Engineering Ideal Atomic Interface for Lithium Ion Storage: Engineering Ideal Atomic Interface for Lithium Ion Storage

A novel strategy for the controlled synthesis of 2D MoS<inf>2</inf>/C hybrid nanosheets consisting of the alternative layer-by-layer interoverlapped single-layer MoS<inf>2</inf> and mesoporous carbon (m-C) is demonstrated. Such special hybrid nanosheets with a maximized MoS<inf>2</inf>/m-C interface contact show very good performance for lithium-ion batteries in terms of high reversible capacity, excellent rate capability, and outstanding cycling stability.

Battery modelling methods for electric vehicles - a review

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are rapidly gaining popularity as a means of de-carbonization in the transport sector in tackling sustainable energy supply and environment pollution problems. To build a proper battery model is essential in predicting battery behaviour under various operating conditions for avoiding unsafe battery operations and developing proper controlling algorithms and maintenance strategies. This paper presents a comprehensive review of battery modelling methods. In particular, the mechanism and characteristics of Li-ion batteries are presented, and different modelling methods are discussed. Considering that equivalent electric circuit models (EECMs) are the most widely used, a detailed analysis of the modelling procedure is presented.

Split Converter-Fed SRM Drive for Flexible Charging in EV/HEV Applications

Electric vehicles (EVs) and hybrid EVs are the way forward for green transportation and for establishing low-carbon economy. This paper presents a split converter-fed four-phase switched reluctance motor (SRM) drive to realize flexible integrated charging functions (dc and ac sources). The machine is featured with a central-tapped winding node, eight stator slots, and six rotor poles (8/6). In the driving mode, the developed topology has the same characteristics as the traditional asymmetric bridge topology but better fault tolerance. The proposed system supports battery energy balance and on-board dc and ac charging. When connecting with an ac power grid, the proposed topology has a merit of the multilevel converter; the charging current control can be achieved by the improved hysteresis control. The energy flow between the two batteries is balanced by the hysteresis control based on their state-of-charge conditions. Simulation results in MATLAB/Simulink and experiments on a 150-W prototype SRM validate the effectiveness of the proposed technologies, which may provide a solution to EV charging issues associated with significant infrastructure requirements.

Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning

BACKGROUND: Research on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to 'fill in the gaps' between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.

RESULTS: We perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.

CONCLUSIONS: This study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed.

Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

The Influence of Cation Structure on the Chemical-Physical Properties of Protic Ionic Liquids

In this study we investigated the influence of five different cations on the physical-chemical properties of protic ionic liquids (PILs) based on bis(trifluoromethanesulfonyl)imide (TFSI-). We showed that the viscosities, ionic conductivities, densities and thermal properties of these PIL are strongly affected by the structure of the protic cation. Furthermore, the influence of the cation structure on the lithium coordination was investigated by Raman spectroscopy for all investigated PIL-based electrolytes for lithium-ion batteries (LIBs). This investigation clearly demonstrates, that the lithium average coordination number in PIL-based electrolytes is strongly affected by (ring) size and the number of protons on the cations structure and, more importantly, it might be significantly lower (more than 60 of that of electrolytes containing aprotic ionic liquids (AILs). Electrochemical performances of these PILs-based electrolytes were then also investigated to dress some conclusion on their applicability for LIB.