• Energy Research

It is generally considered that the representation of a double layer supercapacitor (DLSC) cannot be performed with the usual capacitance and resistance series connected, as it induces a relatively high level of inaccuracy in the results. In multiple previous studies, more advanced models have been developed with very different approaches: models with distributed parameter circuits, based on artificial neural networks (ANNs), fractional order, etc. A non-linear model, less complex than the previous ones and whose behavior adequately represents the DLSCs, is the one formed by a variable capacitance, dependent on its internal voltage. This paper presents a mathematical study to obtain analytical expressions of all the electrical variables of DLSCs, voltage, current, dissipated power and so on, by means of a previous model. This study is carried out considering that the DLSC is charged and discharged through a voltage source and also discharged through a resistor. In later sections, the operational conditions of the DLSC in numerous industrial applications are presented. Finally, a comparative analysis is made between the results produced by the conventional model, with constant capacitance, and the developed model. This analysis is finally followed by the conclusions.

The phenomenon known as the Biefeld-Brown effect or ionic wind has been the subject of study since its discovery with the aim of being applied to aircraft propulsion. Electrohydrodynamic (EHD) thrusters have been developed in a thorough and detailed way since 2000. Subsequently, some attempts have been made to extend them to electric-powered atmospheric aircrafts. This paper is framed in this field by performing a rigorous and detailed analysis of the energy efficiency, measured as the ratio of thrust to energy consumed, for both EHD systems and conventional electric propulsion. This is done using simple EHD thruster configurations together with accurate measurements of the current consumed under controlled environmental conditions. The results are not only compared with the performance of an electric propulsion motor-propeller set, but also consider future research, summarizing the issues that arise to scale them. Future designs of low weight, high performance thrusters might allow this technology to be applied to manned or remotely piloted aircrafts.

In this article, a new methodology for the sizing of a fast-charging station for electric vehicles is presented. The proposed method is applicable to public service vehicles on urban journeys. Its use has been conceived for vehicles equipped with an energy storage system based on supercapacitors (SCs), which are already functional in several countries. The proposed charging station also uses a bank of SCs of variable capacitance. During the study, mathematical expressions will be obtained for the electrical variables involved in vehicle charging: instantaneous current, peak current, charging time, dissipated energy, and the efficiency of energy transference. From these, each of the components of the system will be dimensioned: the capacitance of the charger with its different variable steps, the initial voltage of the charger, and the current smoothing inductor. The proposed charger presents the advantage of allowing energy to be evacuated to the electric vehicle very quickly and with high performance, all without using an external power source or high-power converters. The proposed architecture minimizes the disturbances that, with conventional methods, would appear on the electrical grid, preventing the installation of fast-charging stations at many grid nodes, as is currently the case. Finally, the charger control algorithm is considerably simplified as it only depends on the initial voltage of the vehicle’s accumulator.

Research, Technological Development and Innovation Program Oriented to the Society Challenges of the Spanish Ministry of Economy and Competitiveness [MCIN/AEI/10.13039/501100011033, MCI-20-PID2019-111051RB-I00]; European Union through ERFD Structural Funds (FEDER) through H2020 Research and Innovation programme [864459 (UE-19-TALENT-864459)]