37 resultados para Plug-in electric vehicles

em Universidad Politécnica de Madrid


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A contactless transformer model is proposed in this paper using Finite Element Analysis (FEA). This model can be used to simulate Inductive Coupling Power Transfer (ICPT) systems with good accuracy of the transformer and reduce the fabrication time of these systems. The model not only takes into account the geometry of the windings but also the frequency effects in them. As the transformer does not have a magnetic core, it is complicated to model because the flux is expanded in the area around the windings. In order to obtain a very accurate model, it is necessary to use a 2D/3D field solver.

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High power density is strongly preferable for the on-board battery charger of Plug-in Hybrid Electric Vehicle (PHEV). Wide band gap devices, such as Gallium Nitride HEMTs are being explored to push to higher switching frequency and reduce passive component size. In this case, the bulk DC link capacitor of AC-DC Power Factor Correction (PFC) stage, which is usually necessary to store ripple power of two times the line frequency in a DC current charging system, becomes a major barrier on power density. If low frequency ripple is allowed in the battery, the DC link capacitance can be significantly reduced. This paper focuses on the operation of a battery charging system, which is comprised of one Full Bridge (FB) AC-DC stage and one Dual Active Bridge (DAB) DC-DC stage, with charging current containing low frequency ripple at two times line frequency, designated as sinusoidal charging. DAB operation under sinusoidal charging is investigated. Two types of control schemes are proposed and implemented in an experimental prototype. It is proved that closed loop current control is the better. Full system test including both FB AC-DC stage and DAB DC-DC stage verified the concept of sinusoidal charging, which may lead to potentially very high power density battery charger for PHEV.

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Governments are working in new policies to slow down total energy consumption and greenhouse gases (GHG) emissions, promoting the deployment of electric vehicles (EVs) in all countries. In order to facilitate this deployment and help to reduce the final costs of their batteries, additional utilization of EVs when those are parked has been proposed. EVs can be used to minimize the total electricity cost of buildings (named vehicle to building applications, V2B). In this paper an economic evaluation of EVs in the Building Energy Management System is shown. The optimal storage capacity and its equivalent number of EVs are determined. This value is then used for determining the optimal charging schedule to be applied to the batteries. From this schedule, the total expected profit is derived for the case of a real hotel in Spain.

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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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The decision to select the most suitable type of energy storage system for an electric vehicle is always difficult, since many conditionings must be taken into account. Sometimes, this study can be made by means of complex mathematical models which represent the behavior of a battery, ultracapacitor or some other devices. However, these models are usually too dependent on parameters that are not easily available, which usually results in nonrealistic results. Besides, the more accurate the model, the more specific it needs to be, which becomes an issue when comparing systems of different nature. This paper proposes a practical methodology to compare different energy storage technologies. This is done by means of a linear approach of an equivalent circuit based on laboratory tests. Via these tests, the internal resistance and the self-discharge rate are evaluated, making it possible to compare different energy storage systems regardless their technology. Rather simple testing equipment is sufficient to give a comparative idea of the differences between each system, concerning issues such as efficiency, heating and self-discharge, when operating under a certain scenario. The proposed methodology is applied to four energy storage systems of different nature for the sake of illustration.

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The optical behaviour of cholesteric mixtures of negative dielectric anisotrony under electric fields is reported. A mixture of S 311~ (31.35 %) + N 5 was employed. AC voltages (f = 1000 Hz) betweeen 0 and 150 volts were applied. Cells 23 micron thick, with internal SnO2 electrodes, were used.

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In electric vehicles, passengers sit very close to an electric system of significant power. The high currents achieved in these vehicles mean that the passengers could be exposed to significant magnetic fields. One of the electric devices present in the power train are the batteries. In this paper, a methodology to evaluate the magnetic field created by these batteries is presented. First, the magnetic field generated by a single battery is analyzed using finite elements simulations. Results are compared to laboratory measurements, taken from a real battery, in order to validate the model. After this, the magnetic field created by a complete battery pack is estimated and results are discussed.

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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 studies the effect of different penetration rates of plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EV) in the Spanish electrical system. A stochastic model for the average trip evaluation and for the arriving and departure times is used to determine the availability of the vehicles for charging. A novel advanced charging algorithm is proposed, which avoids any communication among all agents. Its performance is determined through different charging scenarios.

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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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Decreasing the accidents on highway and urban environments is the main motivation for the research and developing of driving assistance systems, also called ADAS (Advanced Driver Assistance Systems). In recent years, there are many applications of these systems in commercial vehicles: ABS systems, Cruise Control (CC), parking assistance and warning systems (including GPS), among others. However, the implementation of driving assistance systems on the steering wheel is more limited, because of their complexity and sensitivity. This paper is focused in the development, test and implementation of a driver assistance system for controlling the steering wheel in curve zones. This system is divided in two levels: an inner control loop which permits to execute the position and speed target, softening the action over the steering wheel, and a second control outer loop (controlling for fuzzy logic) that sends the reference to the inner loop according the environment and vehicle conditions. The tests have been done in different curves and speeds. The system has been proved in a commercial vehicle with satisfactory results.

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The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.

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In hybrid and electric vehicles, passengers sit very close to an electric system of significant power, which means that they may be subjected to high electromagnetic fields. The hazards of long-term exposure to these fields must be taken into account when designing electric vehicles and their components. Among all the electric devices present in the power train, the electronic converter is the most difficult to analyze, given that it works with different frequencies. In this paper, a methodology to evaluate the magnetic field created by a power electronics converter is proposed. After a brief overview of the recommendations of electromagnetic fields exposure, the magnetic field produced by an inverter is analyzed using finite element techniques. The results obtained are compared to laboratory measurements, taken from a real inverter, in order to validate the model. Finally, results are used to draw some conclusions regarding vehicle design criteria and magnetic shielding efficiency.

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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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In this paper the daily temporal and spatial behavior of electric vehicles (EVs) is modelled using an activity-based (ActBM) microsimulation model for Flanders region (Belgium). Assuming that all EVs are completely charged at the beginning of the day, this mobility model is used to determine the percentage of Flemish vehicles that cannot cover their programmed daily trips and need to be recharged during the day. Assuming a variable electricity price, an optimization algorithm determines when and where EVs can be recharged at minimum cost for their owners. This optimization takes into account the individual mobility constraint for each vehicle, as they can only be charged when the car is stopped and the owner is performing an activity. From this information, the aggregated electric demand for Flanders is obtained, identifying the most overloaded areas at the critical hours. Finally it is also analyzed what activities EV owners are underway during their recharging period. From this analysis, different actions for public charging point deployment in different areas and for different activities are proposed.