Space Race: An Interactive Digital Tool in the Classroom. Are You Ready?

This document presents an interdisciplinary teaching experience based on Game-based Learning as an educational methodology complementary to the Flipped Classroom pedagogical approach in higher education. The tool used was the Space Race application integrated into the free Socrative software. A more active and meaningful learning has been promoted in the student with its implementation. Likewise, it has allowed the face-to-face classes to be energized, creating a relaxed atmosphere. The reflective and critical use of technological applications and mobile devices in the classroom has also been encouraged. The use of the Space Race has increased the participation of students in the classroom, their motivation and interest, collaborating in the development of skills and abilities. This tool has been very useful to obtain bidirectional teacher-student feedback in real time. As a result, a more cooperative, reflective and meaningful learning has been obtained

A Review of Transverse Flux Machines Topologies and Design

High torque and power density are unique merits of transverse flux machines (TFMs). TFMs are particularly suitable for use in direct-drive systems, that is, those power systems with no gearbox between the electric machine and the prime mover or load. Variable speed wind turbines and in-wheel traction seem to be great-potential applications for TFMs. Nevertheless, the cogging torque, efficiency, power factor and manufacturing of TFMs should still be improved. In this paper, a comprehensive review of TFMs topologies and design is made, dealing with TFM applications, topologies, operation, design and modeling

Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor

Transverse flux motors (TFMs) are being investigated to be used in vehicle traction applications due to their high torque density. In this paper, a two-phase axial-gap transverse flux motor is designed for an electric scooter, proposing a novel analytical design method. First, the dimensioning equations of the motor are obtained based on the vehicle requirements, and the stationary dq model is calculated. Then, the motor is optimized using a multiobjective genetic algorithm, and finally a 3D-FEM verification is made. Both the motor structure and the design method aim to have a low complexity, in order to favor the sizing and manufacturing processes through a low computation time and simple core shapes. This approach has not yet been explored in axial-gap TFMs

Flipped teaching and interactive tools. A multidisciplinary innovation experience in higher education

[EN] Nowadays learning methods in higher education are under a constant review process. Applications focused on Blended-Learning allow to speed-up the learning process; this facilitates the design and implementation of interactive resources in the classroom. The present study shows an experience developed with engineering master students. Flipped Teaching approach has achieved significant mention in academic circles in recent years. Undoubtedly, the implementation of this educational methodology improves students’ motivation and increases their participation in the classroom. In this paper different Information and Communication Technologies (ICT) tools and multimedia resources that facilitate the teaching sessions are presented. Its use has been simple and intuitive. These educational tools increase the skills, abilities and competences acquired by students. The objective is to achieve more interactive learning. Students positively value this activities related to the Flipped Learning. In addition, students prefer teaching-learning procedures more dynamic, flexible, creative, participatory and with continuous evaluation. Although the general impression is that they need more effort and more dedication, compared to the Traditional Teaching. Every time there is a greater number of educational tools and electronic devices for higher education. However, its use must be correct so that it can be useful in training students.Artal-Sevil, JS.; Gargallo-Castel, AF.; Valero-Gracia, MS. (2020). Flipped teaching and interactive tools. A multidisciplinary innovation experience in higher education. En 6th International Conference on Higher Education Advances (HEAd'20). Editorial Universitat Politècnica de València. (30-05-2020):103-112. https://doi.org/10.4995/HEAd20.2020.10990OCS10311230-05-202

Design of small-scale hybrid energy systems taking into account generation and demand uncertainties

The adoption of energy systems powered by renewable sources requires substantial economic investments. Hence, selecting system components of an appropriate size becomes a critical step, which is significantly influenced by their distinct characteristics. Furthermore, the availability of renewable energy varies over time, and estimating this availability introduces considerable uncertainty. In this paper, we present a technique for the optimal design of hybrid energy systems that accounts for the uncertainty associated with resource estimation. Our method is based on stochastic programming theory and employs a surrogate model to estimate battery lifespan using a feedforward neural network (FFNN). The optimization analysis for system design was conducted using a genetic algorithm (GA) and the poplar optimization algorithm (POA). We assessed the effectiveness of the proposed technique through a hypothetical case study. The introduction of a surrogate model, based on an FFNN, resulted in an approximation error of 9.6 % for cost estimation and 20.6 % for battery lifespan estimation. The probabilistic design indicates an energy system cost that is 25.7 % higher than that obtained using a deterministic approach. Both the GA and POA achieved solutions that likely represent the global optimum

Searching for promisingly trained artificial neural networks

Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to construct the probability distribution of the learning error of an ANN designed for short-term forecasting. The training and validation processes were conducted multiple times, each time considering a unique random starting point, and the subsequent forecasting error was calculated one step ahead. From this, we ascertained the probability of having obtained all the local optima. Our extensive computational analysis involved training a shallow feedforward neural network (FFNN) using wind power and load demand data from the transmission systems of the Netherlands and Germany. Furthermore, the analysis was expanded to include wind speed prediction using a long short-term memory (LSTM) network at a site in Spain. The improvement gained from the FFNN, which has a high probability of being the global optimum, ranges from 0.7% to 8.6%, depending on the forecasting variable. This solution outperforms the persistent model by between 5.5% and 20.3%. For wind speed predictions using an LSTM, the improvement over an average-trained network stands at 9.5%, and is 6% superior to the persistent approach. These outcomes suggest that the advantages of exhaustive search vary based on the problem being analyzed and the type of network in use. The MCS method we implemented, which estimates the probability of identifying all local optima, can act as a foundational step for other techniques like Bayesian model selection, which assumes that the global optimum is encompassed within the available hypotheses

A Comprehensive Analytical Sizing Methodology for Transverse and Radial Flux Machines

Transverse flux machines have the potential to offer high torque density in direct-drive vehicle traction applications. Besides, sizing equations are a wide-spread technique for transverse flux machines design, as their computational cost is much lower than the finite element method. In this paper a novel analytical sizing methodology for transverse and radial flux machines is presented, focusing on the current load and the pole length factor as the main design parameters. The motor specifications are intended for a light-duty electric vehicle application. As transverse flux machines have a single, hoop-shaped coil per phase that embraces the flux of all the pole pairs, their principle of operation and therefore their sizing equations differ from radial flux machines. The proposed analytical method allows to compare transverse and radial flux machines easily through a similarity analysis and a parametric study. Furthermore, the discrepancies between the analytical model and the finite element method are quantified and then included in previous equations. Then the analytical model is optimized with a multiobjective genetic algorithm in the final stage. According to the sizing methodology presented here, transverse flux machines have a superior performance than radial flux machines in terms of torque density and efficiency

Modelado y control de un motor de imanes permanentes aplicado a un vehículo de movilidad personal.

El presente documento tiene por objeto el desarrollo de diferentes algoritmos de control aplicados al sistema de tracción de un vehículo de movilidad personal. Con el fin de justificar la aportación de este trabajo fin de máster, se realizó una investigación acerca de los avances que se han llevado a cabo en el control de vehículos eléctricos, tanto con técnicas de control difuso como con técnicas de control basadas en redes neuronales. Debido a la dificultad de encontrar una hoja de datos en la que se especificaran todos los parámetros del motor, se realiza un diseño preliminar partiendo de las especificaciones generales del patín analizado. El modelo del sistema de tracción del patín se desarrolla usando la herramienta Matlab-Simulink y los controles que se van a analizar y comparar son los siguientes: control PI (usado como técnica de control de referencia), control fuzzy y control neural. Para los tres controles desarrollados se lleva a cabo un análisis y una comparación de la respuesta dinámica obtenida, en la que se comparan tres datos objetivos como son el tiempo de respuesta, la sobreoscilación y el error de velocidad. <br /

Estudio, modelado y verificación de arquitecturas no aisladas de procesamiento parcial de potencia.

El trabajo se centra en el estudio de topologías de procesado parcial de potencia para analizar los beneficios de esta tecnología frente a topologías clásicas. Además, se realizan modelados promediados de varios convertidores, análisis de su rendimiento y verificación experimental para finalmente establecer una serie de conclusiones acerca de qué topologías presentan mejoras.<br /

Modelado y control de una prótesis robótica mediante sensores EMG y la plataforma Raspberry-Pi.

Los objetivos principales de este proyecto son entonces, el rediseño, impresión y montaje de una prótesis 3D OpenSource, el estudio e implementación de diferentes sensores para dotar a la prótesis de mayor capacidad de interacción con el entorno, el diseño e implementación del control de diferentes tipos de agarre y el diseño del control de la prótesis mediante redes neuronales.<br /