The main goal of EP4H2 project is to provide innovative technologies that allow to increase efficiency and flexibility of hidrogen electrolyzers, while reducing their cost, which will utlimately allow to advance towards the production of Green Hydrogen. The Consortium of the project is composed by Tecnalia R&I, Ingeteam, Mondragon Unibertsitatea and the UPV/EHU.

A HardWare Implementation of the PWM inspired encoding/decoding algorithm (IHA-PWM). A new supervised training approach of SNN for regression based on both backpropagation and PWM inspired encoding/decoding algorithm. Define the specification for a neuromorphic HardWare implementation of both IHA-PWM and the new supervised training algorithm.

As part of the grinding process, the aim of this project is to implement a hybrid model in which the artificial neural networks are a necessary complement to the analytic models.  In particular, this approach allows for obtaining parameters of the models that are closer to reality and that allow for, as well as improved knowledge of the process, better simulation of its behaviour with the waiting time of the machine. transfer rumours Thus, we propose the design of an intelligent system capable of estimating the...