A Secondary-Side Controlled Electric Vehicle Wireless Charger

Corti, Fabio; Reatti, Alberto; Nepote, Andrea; Pugi, Luca; Pierini, Marco; Paolucci, Libero; Grasso, Francesco; Grasso, Emanuele; Nienhaus, Matthias

doi:10.3390/en13246527

Cited by 35 publications

(14 citation statements)

References 17 publications

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“…To increase the system efficiency, several methods have been proposed. Some of them concern the resonance frequency tuning [6,33], others deal with the tuning of the resonance capacitance to adapt the reactive power compensation during the EV motion [34][35][36], while in [37] the authors focused on keeping the output power stable by working on an optimization method to improve the system efficiency and regulating the output voltage.…”

Section: Focus On the Magnetic Couplermentioning

confidence: 99%

Optimal Coupler Topology for Dynamic Wireless Power Transfer for Electric Vehicle

et al. 2021

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Recently, the number of electric vehicles (EVs) is increasing due to the decline of oil resources and the rising of greenhouse gas emissions. However, EVs have not received full acceptance by consumers due to the limitations of the stored energy and charging problems. The dynamic or in-motion charging solution has become a suitable choice to solve the battery-related issues. Many researchers and vehicle manufacturers are working to develop an efficient charging system for EVs. In order to improve the efficiency of the dynamic wireless power transfer (DWPT), the electromagnetic coupling coefficient between the two parts of the coupler must be maximized. This paper was dedicated to find the optimal topology of a magnetic coupler with the best coupling factor while taking in consideration the displacement and the misalignment of the EV. The article is introduced by developing a methodology for characterizing the electrical parameters of couplers, followed by a comparative study of different forms of coils suitable for dynamic charging of electric vehicles. The particularity of the proposed study concerned the overall dimensions, or the areas occupied by the windings of the coils remaining the same for all the chosen shapes and corresponding to the surface that is actually available under the EV. Simulation and experimental tests were carried out to validate the proposed study.

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Section: Focus On the Magnetic Couplermentioning

confidence: 99%

Optimal Coupler Topology for Dynamic Wireless Power Transfer for Electric Vehicle

et al. 2021

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“…This limitation can be overcome by installing a DC/DC converter [50,51] or a controlled rectifier that, depending on its topology, allows the flow of energy in both directions. Both options work as a battery impedance adapter [52], which helps with a suitable control strategy to improve the efficiency of the process [53].…”

Section: Model For Ev Bidirectional Wireless Chargermentioning

confidence: 99%

Review on Control Techniques for EV Bidirectional Wireless Chargers

2021

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Due to their flexibility, Electric Vehicles (EVs) constitute an important asset for the integration of renewable energy sources in the Smart Grid. In particular, they should have a dual role: as a controllable load and as a mobile generator with a low inertia. To perform these tasks, chargers must provide the electronics with a power flow from the grid to the vehicle and vice versa. This bidirectionality can also be implemented in wireless chargers. The power converters, the compensation networks and the coil misalignment must be considered when designing the control of these systems. This paper presents a review about the proposed algorithms to control the active and the reactive power flow in a bidirectional wireless charger.

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“…Hence, several efforts are being made in order to optimize solar energy production, transmission and storage. This latest aspect is of main importance since it is not only performed through a dedicated accumulator (e.g., batteries), but it includes novel solutions such as using electrical vehicles as mobile storage devices [1]. Indeed, in this case it is important to optimize power transfer efficiency [2].…”

Section: Introductionmentioning

confidence: 99%

Power Forecasting of a Photovoltaic Plant Located in ENEA Casaccia Research Center

et al. 2021

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This work proposes an Artificial Neural Network (ANN) able to provide an accurate forecasting of power produced by photovoltaic (PV) plants. The ANN is customized on the basis of the particular season of the year. An accurate analysis of input variables, i.e., solar irradiance, temperature and air humidity, carried out by means of Pearson Correlation, has allowed to select, day by day, the most suitable set of inputs and ANN architecture also to reduce the necessity of large computational resource. Thus, features are added to the ANN as needed, avoiding waste of computational resources. The method has been validated through data collected from a PV plant installed in ENEA (National agency for new technologies, energy and sustainable economic development) Research Center, located in Casaccia, Rome (Italy). The developed strategy is able to furnish accurate predictions even in the case of strong irregularities of solar irradiance, providing accurate results in rapidly changing scenarios.

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A Secondary-Side Controlled Electric Vehicle Wireless Charger

Cited by 35 publications

References 17 publications

Optimal Coupler Topology for Dynamic Wireless Power Transfer for Electric Vehicle

Optimal Coupler Topology for Dynamic Wireless Power Transfer for Electric Vehicle

Review on Control Techniques for EV Bidirectional Wireless Chargers

Power Forecasting of a Photovoltaic Plant Located in ENEA Casaccia Research Center

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