73 resultados para electric guitar


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and on is a short instrumental featuring a nylon stringed acoustic guitar with an echo, chorus and tap reverb added to the tail, piano, and two synth pads.

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Atmos (Piano and Guitar) is a short instrumental with piano and guitar.

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Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

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It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

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We prove that the vorticity or the expansion vanishes for any shear-free perfect fluid solution of the Einstein field equations where the pressure satisfies a barotropic equation of state and the spatial divergence of the electric part of the Weyl tensor is zero.

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The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control.

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Concentrated electric field is crucial in generation of needleless electrospinning; the electric field profile together with electric field intensity of the spinneret directly affect the needleless electrospinning performance. Understanding the electric field of different spinnerets would definitely benefit the design and optimization of needleless electrospinning. Three-dimensional (3D) finite element analysis has been used to analyze the electric field profile and electric field intensity of different spinnerets for needleless electrospinning by using the simulation software COMSOL Multiphysics 3.5a. It has been found that evolution of the spinneret of needleless electrospinning from cylinder to multiple disks and then to multiple rings results in stronger and more concentrated electric field. The analysis based on 3D simulation of the electric field could benefit further development of needleless electrospinning in which the production rate and quality of as-spun nanofibers are of great importance.

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In this study, the suspension of MoO3 nanobelts was first prepared in a hydrothermal way from Mo powders and H2O2 solution, which could be transformed into the suspension of HxMoO3 nanobelts under an acidic condition using N2H4 ·H2O as the reducing agent. Three paper-form samples made from MoO3 and HxMoO3 nanobelts (low or high hydrogen content) were then fabricated via a vacuum filtration method, followed by their structural comparative analysis such as FESEM, XRD, Raman spectra, and XPS, etc. The measurement of electric resistances at room temperature shows that the conductance of HxMoO3 nanobelts is greatly improved because of hydrogen doping. The temperature-dependent resistances of HxMoO3 nanobelts agree with the exponential correlation, supporting that the conducting carriers are the quasi-free electrons released from Mo5+. In addition, the formation process of HxMoO3 nanobelts from MoO3 nanobelts is also discussed.

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A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

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