The present work aims at quantifying how, and how much, the uncertainties on the components and material parameters of a wireless power transfer (WPT) system for the static charge of electric vehicles affect the overall efficiency and functionality of the final produced device. With the aim of considering the perspective of a possible industrial developer, the parameters selected for the uncertainty quantification are chosen to be the capacitance values of the compensation capacitors and the electromagnetic material parameters used for the construction of the magnetic structure of a WPT system, i.e. the parameters of the elements to be purchased. The analysis is based on a standard system among the ones provided by the current SAE J2954 recommended practice.

A 5 kW ICPT system with a large air gap of 20 cm has been developed and built for a battery charger of electric vehicles. The practical sizing, the best compensation topology and the operational frequency have been studied in order to get the maximum efficiency of the system. The study has been focused in showing the process of the prototype's implementation, validating the theoretical results and analyzing the influence of the frequency deviation with respect to the resonant frequency and the variation of the distance between the two coils in the behaviour of the system.

For pure electric vehicles can reach the expected development and have become an alternative to conventional or hybrid vehicles, it is still necessary to solve various problems. The most important are to increase the autonomy of the vehicle and make charging process as quick and clean as possible. Inductive power transfer systems (IPT) can be the solution to these problems, on the one hand, the weight and size limitations of the batteries required for adequate autonomy can be solved with sufficient load points on public roads that allow "recharge" more frequently batteries or even the possibility that these are loaded by dedicated lanes moving. This is only feasible if the loading process requires no human intervention the maneuver faster and safe for the driver. Furthermore, the ability to recharge the batteries of a contactless EV is now a reality, as evidenced by the high number of patents and published papers, however, for these systems to be part of our daily lives, we need to meet strict international standards for human exposure to electromagnetic fields and, for this, the vehicle must be properly shielded. This paper shows the experimental development of a 30 kW inductive charger with shielding system and the results obtained.

The increasing interest in the use of renewable energy sources for the generation of electrical energy makes it necessary to ensure that these type of installations do not jeopardize the global operation of the electrical system to which they are connected. Up until now, this safety has been achieved by imposing very strict limits to the percentage of “non-controllable” renewable energy that can be connected to the grid. In order to increase these limits, new control schemes must be developed, focusing in power quality and, if possible, in trying to help grid stability. The paper proposes two new control methods for the current injected by a variable-speed generation system and compares them to a traditional hysteresis control. The first one obtains a table by using an algorithm that calculates the switching state that minimises switching frequency. The commutation is determined by a single comparator applied to the error vector, achieving a circular error area. The use of this table, along with the selection of a circular error area for the current vector makes that the current error remains always inside the specified error area. The second method is a predictive one, based on the previous one, that decides the optimum switching vector in the precise time when the commutation occurs, taking into account the present state of the system.

Validating wireless power transfer (WPT) systems for electric vehicles (EVs) is a challenge due to efficiency variations caused by coil misalignments and height differences arising from various vehicle designs. Traditional simulation methods, such as finite element analysis (FEM), provide high accuracy but entail significant computational costs and calculation times, limiting the number of case studies and their optimization. This paper presents a methodology that integrates Machine Learning (ML) and Genetic Algorithms (GA) to overcome these limitations. An ML model rapidly and accurately predicts key electromagnetic parameters across a wide range of positions and frequencies. These predictions feed into a GA that optimizes control variables (voltages and frequency) with the objective of maximizing power transfer efficiency, while simultaneously ensuring component integrity at each operating point. Beyond drastically reducing simulation time and experimental effort, this methodology will enable knowledge extraction and its use for formulating design rules. These rules can lay the groundwork for developing simplified, real-time adaptive control strategies, facilitating the reduction of control variables and the narrowing of search ranges.

The implantation of the Internet technologies in the industrial world is a reality that grows of exponential form. This paper presents the design and implementation of an application for real-time visualization of the state and the program of Programmable Logic Controllers (PLCs), using Java and Extended Mark-up Language (XML) technology. This application allows the visualization of PLC programs without the programming software. This visualization follows the IEC 61131 standard for PLC programming. The application is written in three versions: Applet, Java application and Web application. It is possible the simultaneous visualization of several PLC programs.