387 resultados para hybrid electric vehicles


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The paper presents results of comparative investigation of carbon nanotubes growth processes in dense low-temperature plasma and on substrate surface. Hybrid/Monte-Carlo numerical simulations were used to demonstrate the differences in the ion fluxes, growth rates and kinetics of adsorbed atoms re-distribution on substrate and nanotubes surfaces. We show that the plasma parameters significantly affect the nanotubes growth kinetics. We demonstrate that the growth rates of the nanotubes in plasma and on surface can differ by three orders, and the specific fluxes to the nanotube in the plasma can exceed the flux to surface-grown nanotube by six orders. We also show that the metal catalyst used for the nanotubes production on surface and in arc is a subject to very different conditions and this may be a key factor for the nanotube growth mode. The obtained dependencies for the ion fluxes to the nanotubes and nanotubes growth rates on the plasma parameters may be useful for selection of the production methods.

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A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

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(Figure Presented) Unusual conductivity effects: Suitably functionalized dendrimers (see picture) are capable of forming truly covalent three-dimensional networks with remarkably high conductivity on electrochemical doping. Depending on the charging level of the electroactive components used as building blocks for the dendrimer core and the perimeter, two separated regimes of electrical conductivity can be observed.

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The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

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Abstract Ag-TiO2 and Au-TiO2 hybrid electrodes were designed by covalent attachment of TiO2 nanoparticles to Ag or Au electrodes via an organic linker. The optical and electronic properties of these systems were investigated using the cytochrome b5 (Cyt b5) domain of sulfite oxidase, exclusively attached to the TiO2 surface, as a Raman marker and model redox enzyme. Very strong SERR signals of Cyt b 5 were obtained for Ag-supported systems due to plasmonic field enhancement of Ag. Time-resolved surface-enhanced resonance Raman spectroscopic measurements yielded a remarkably fast electron transfer kinetic (k = 60 s -1) of Cyt b5 to Ag. A much lower Raman intensity was observed for Au-supported systems with undefined and slow redox behavior. We explain this phenomenon on the basis of the different potential of zero charge of the two metals that largely influence the electronic properties of the TiO2 island film. © 2013 American Chemical Society.

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Hybrid powerplants combining internal combustion engines and electric motor prime movers have been extensively developed for land- and marine-based transport systems. The use of such powerplants in airborne applications has been historically impractical due to energy and power density constraints. Improvements in battery and electric motor technology make aircraft hybrid powerplants feasible. This paper presents a technique for determining the feasibility and mechanical effectiveness of powerplant hybridisation. In this work, a prototype aircraft hybrid powerplant was designed, constructed and tested. It is shown that an additional 35% power can be supplied from the hybrid system with an overall weight penalty of 5%, for a given unmanned aerial system. A flight dynamic model was developed using the AeroSim Blockset in MATLAB Simulink. The results have shown that climb rates can be improved by 56% and endurance increased by 13% when using the hybrid powerplant concept.

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The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.