965 resultados para electric energy


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The formation of electric potential over lunar magnetized regions is essential for understanding fundamental lunar science, for understanding the lunar environment, and for planning human exploration on the Moon. A large positive electric potential was predicted and detected from single point measurements. Here, we demonstrate a remote imaging technique of electric potential mapping at the lunar surface, making use of a new concept involving hydrogen neutral atoms derived from solar wind. We apply the technique to a lunar magnetized region using an existing dataset of the neutral atom energy spectrometer SARA/CENA on Chandrayaan-1. Electrostatic potential larger than +135 V inside the Gerasimovic anomaly is confirmed. This structure is found spreading all over the magnetized region. The widely spread electric potential can influence the local plasma and dust environment near the magnetic anomaly.

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There is still discussion regarding whether liquid biofuels can contribute to rural energy security in the global South. We argue that transitioning to a village energy supply based on jatropha hedges around smallholder plots is possible, but requires collective effort for the acquisition and maintenance of processing equipment and for the running of village generators. The use of jatropha oil for lighting in rural households is affordable and technically possible, but not ideal if more efficient electric solutions exist. Cooking with jatropha oil or press cake is also possible, but quantities produced in hedges can only substitute a small part of the firewood used by rural households.

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Engineers are confronted with the energy demand of active medical implants in patients with increasing life expectancy. Scavenging energy from the patient’s body is envisioned as an alternative to conventional power sources. Joining in this effort towards human-powered implants, we propose an innovative concept that combines the deformation of an artery resulting from the arterial pressure pulse with a transduction mechanism based on magneto-hydrodynamics. To overcome certain limitations of a preliminary analytical study on this topic, we demonstrate here a more accurate model of our generator by implementing a three-dimensional multiphysics finite element method (FEM) simulation combining solid mechanics, fluid mechanics, electric and magnetic fields as well as the corresponding couplings. This simulation is used to optimize the generator with respect to several design parameters. A first validation is obtained by comparing the results of the FEM simulation with those of the analytical approach adopted in our previous study. With an expected overall conversion efficiency of 20% and an average output power of 30 μW, our generator outperforms previous devices based on arterial wall deformation by more than two orders of magnitude. Most importantly, our generator provides sufficient power to supply a cardiac pacemaker.

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Replacement intervals of implantable medical devices are commonly dictated by battery life. Therefore, intracorporeal energy harvesting has the potential to reduce the number of surgical interventions by extending the life cycle of active devices. Given the accumulated experience with intravascular devices such as stents, heart valves, and cardiac assist devices, the idea to harvest a small fraction of the hydraulic energy available in the cardiovascular circulation is revisited. The aim of this article is to explore the technical feasibility of harvesting 1 mW electric power using a miniature hydrodynamic turbine powered by about 1% of the cardiac output flow in a peripheral artery. To this end, numerical modelling of the fluid mechanics and experimental verification of the overall performance of a 1:1 scale friction turbine are performed in vitro. The numerical flow model is validated for a range of turbine configurations and flow conditions (up to 250 mL/min) in terms of hydromechanic efficiency; up to 15% could be achieved with the nonoptimized configurations of the study. Although this article does not entail the clinical feasibility of intravascular turbines in terms of hemocompatibility and impact on the circulatory system, the numerical model does provide first estimates of the mechanical shear forces relevant to blood trauma and platelet activation. It is concluded that the time-integrated shear stress exposure is significantly lower than in cardiac assist devices due to lower flow velocities and predominantly laminar flow.

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Luminescence and energy transfer in [Zn1-xRux(bpy)3][NaAl1-yCry(ox)3] (x ≈ 0.01, y = 0.006 − 0.22; bpy = 2,2‘-bipyridine, ox = C2O42-) and [Zn1-x-yRuxOsy(bpy)3][NaAl(ox)3] (x ≈ 0.01, y = 0.012) are presented and discussed. Surprisingly, the luminescence of the isolated luminophores [Ru(bpy)3]2+ and [Os(bpy)3]2+ in [Zn(bpy)3][NaAl(ox)3] is hardly quenched at room temperature. Steady-state luminescence spectra and decay curves show that energy transfer occurs between [Ru(bpy)3]2+ and [Cr(ox)3]3- and between [Ru(bpy)3]2+ and [Os(bpy)3]2+ in [Zn1-xRux(bpy)3][NaAl1-yCry(ox)3] and [Zn1-x-yRuxOsy(bpy)3] [NaAl(ox)3], respectively. For a quantitative investigation of the energy transfer, a shell type model is developed, using a Monte Carlo procedure and the structural parameters of the systems. A good description of the experimental data is obtained assuming electric dipole−electric dipole interaction between donors and acceptors, with a critical distance Rc for [Ru(bpy)3]2+ to [Cr(ox)3]3- energy transfer of 15 Å and for [Ru(bpy)3]2+ to [Os(bpy)3]2+ energy transfer of 33 Å. These values are in good agreement with those derived using the Förster−Dexter theory.

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Experiments searching for weak interacting massive particles with noble gases such as liquid argon require very low detection thresholds for nuclear recoils. A determination of the scintillation efficiency is crucial to quantify the response of the detector at low energy. We report the results obtained with a small liquid argon cell using a monoenergetic neutron beam produced by a deuterium-deuterium fusion source. The light yield relative to electrons was measured for six argon recoil energies between 11 and 120 keV at zero electric drift field.

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In developing economies, consumption of electricity in residential and commercial sectors increased with economic development. In order to identify the factors for effective facilitation of standard and labeling programs, this article explores factors that affect consumer choice to energy-efficient products. Main findings are as follows: (1)Consumers in Thailand shows the highest awareness to environmental friendly concepts, followed by India and China.(2) Chosen labeled products include air-conditioners, TVs, refrigerators and washing machines, but not some popular products such as ceiling fans, electric fans or mobile phones. (3) Consumer who has higher energy conservation perception will buy energy efficient products.(4) Consumers in China, India and Thailand are sensitive to energy efficiency of products, primarily because they lead to less expenditure on electricity. (5) Labeling works to make levels of the energy efficiency of products more visible and thus helped consumers to choose the products.

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The design of an electrodynamic tether is a complex task that involves the control of dynamic instabilities, optimization of the generated power (or the descent time in deorbiting missions), and minimization of the tether mass. The electrodynamic forces on an electrodynamic tether are responsible for variations in the mechanical energy of the tethered system and can also drive the system to dynamic instability. Energy sources and sinks in this system include the following: 1) ionospheric impedance, 2) the potential drop at the cathodic contactor, 3) ohmic losses in the tether, 4) the corotational plasma electric field, and 5) generated power and/or 6) input power. The analysis of each of these energy components, or bricks, establishes parameters that are useful tools for tether design. In this study, the nondimensional parameters that govern the orbital energy variation, dynamic instability, and power generation were characterized, and their mutual interdependence was established. A space-debris mitigation mission was taken as an example of this approach for the assessment of tether performance. Numerical simulations using a dumbbell model for tether dynamics, the International Geomagnetic Reference Field for the geomagnetic field, and the International Reference Ionosphere for the ionosphere were performed to test the analytical approach. The results obtained herein stress the close relationships that exist among the velocity of descent, dynamic stability, and generated power. An optimal tether design requires a detailed tradeoff among these performances in a real-world scenario.

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The variation in the adoption of a technology as a major source of competitive advantage has been attributed to the wide-ranging strategic foresight and the integrative capability of a firm. These possible areas of competitive advantage can exist in the periphery of the firm's strategic vision and can get easily blurred as a result of rigidness and can permeate in the decision-making process of the firm. This article explores how electric utility firms with a renewable energy portfolio can become strategically rigid in terms of adoption of newer technologies. The reluctance or delay in the adoption of new technology can be characterized as strategic rigidness, brought upon as a result of a firm's core competence or core capability in the other, more conventional technology arrangement. This paper explores the implications of such rigidness on the performance of a firm and consequently on the energy eco-system. The paper substantiates the results by emphasizing the case of Iberdrola S.A., an incumbent firm as a wind energy developer and its adoption decision behavior. We illustrate that the very routines that create competitive advantage for firms in the electric utility industry are vulnerable as they might also develop as sources of competitive disadvantage, when firms confront environmental change and uncertainty.

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This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From this information, the total storage capacity per zone is evaluated and some strategies for EV aggregator are proposed, allowing the aggregator to fulfill bids on the electricity markets.

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Batteries and ultracapacitors for hybrid and electric vehicles must satisfy very demanding working conditions that are not usual in other applications. In this sense, specific tests must be performed in order to draw accurate conclusions about their behaviour. To do so, new advanced test benches are needed. These platforms must allow the study of a wide variety of energy storage systems under conditions similar to the real ones. In this paper, a flexible, low-cost and highly customizable system is presented. This system allows batteries and ultracapacitors to be tested in many and varied ways, effectively emulating the working conditions that they face in an electric vehicle. The platform was specifically designed to study energy storage systems for electric and hybrid vehicles, meaning that it is suitable to test different systems in many different working conditions, including real driving cycles. This flexibility is achieved keeping the cost of the platform low, which makes the proposed test bench a feasible alternative for the industry. As an example of the functionality of the platform, a test consisting of a 17-minute ARTEMIS urban cycle with a NiMH battery pack is presented.

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This paper presents a novel vehicle to vehicle energy exchange market (V2VEE) between electric vehicles (EVs) for decreasing the energy cost to be paid by some users whose EVs must be recharged during the day to fulfil their daily scheduled trips and also reducing the impact of charging on the electric grid. EVs with excess of energy in their batteries can transfer this energy among other EVs which need charge during their daily trips. These second type of owners can buy the energy directly to the electric grid or they can buy the energy from other EV at lower price. An aggregator is responsible for collecting all information among vehicles located in the same area at the same time and make possible this energy transfer.

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One of the main objectives of European Commission related to climate and energy is the well-known 20-20-20 targets to be achieved in 2020: Europe has to reduce greenhouse gas emissions of at least 20% below 1990 levels, 20% of EU energy consumption has to come from renewable resources and, finally, a 20% reduction in primary energy use compared with projected levels, has to be achieved by improving energy efficiency. In order to reach these objectives, it is necessary to reduce the overall emissions, mainly in transport (reducing CO2, NOx and other pollutants), and to increase the penetration of the intermittent renewable energy. A high deployment of battery electric (BEVs) and plug-in hybrid electric vehicles (PHEVs), with a low-cost source of energy storage, could help to achieve both targets. Hybrid electric vehicles (HEVs) use a combination of a conventional internal combustion engine (ICE) with one (or more) electric motor. There are different grades of hybridation from micro-hybrids with start-stop capability, mild hybrids (with kinetic energy recovery), medium hybrids (mild hybrids plus energy assist) and full hybrids (medium hybrids plus electric launch capability). These last types of vehicles use a typical battery capacity around 1-2 kWh. Plug in hybrid electric vehicles (PHEVs) use larger battery capacities to achieve limited electric-only driving range. These vehicles are charged by on-board electricity generation or either plugging into electric outlets. Typical battery capacity is around 10 kWh. Battery Electric Vehicles (BEVs) are only driven by electric power and their typical battery capacity is around 15-20 kWh. One type of PHEV, the Extended Range Electric Vehicle (EREV), operates as a BEV until its plug-in battery capacity is depleted; at which point its gasoline engine powers an electric generator to extend the vehicle's range. The charging of PHEVs (including EREVs) and BEVs will have different impacts to the electric grid, depending on the number of vehicles and the start time for charging. Initially, the lecture will start analyzing the electrical power requirements for charging PHEVs-BEVs in Flanders region (Belgium) under different charging scenarios. Secondly and based on an activity-based microsimulation mobility model, an efficient method to reduce this impact will be presented.

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Electric vehicles constitute a multidisciplinary subject that involves disciplines such as automotive, mechanical, electrical and control engineering. Due to this multidisciplinary technical nature, practical teaching methodologies are of special relevance. Paradoxically, in the past, the training of engineers specializing in this area has lacked the practical component represented by field tests, due to the difficulty of accessing real systems. This paper presents an educational project specifically designed for the teaching and training of engineering students with different backgrounds and experience. The teaching methodology focuses on the topology of electric traction drives and their control. It includes two stages, a simulation computer model and a scaled laboratory workbench that comprises a traction electrical drive coupled to a vehicle emulator. With this equipment, the effectiveness of different traction control strategies can be analyzed from the point of view of energy efficiency, robustness, easiness of implementation and acoustic noise.

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In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.