@inproceedings{9243111,

title = {Battery state prediction in photovoltaic standalone installations},

author = {A Guillén-Asensio and I Sanz-Gorrachategui and P Pastor-Flores and J S Artal-Sevil and Antonio Bono and Bonifacio Martín del Brío and C Bernal-Ruiz},

doi = {10.1109/EVER48776.2020.9243111},

year  = {2020},

date = {2020-09-01},

booktitle = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)},

pages = {1-6},

abstract = {Effective energy treatment is one of the challenges to which scientists are devoting more interest and resources. Currently, there is a need to optimize the generation of energy by renewable methods and to improve the storage and management of battery cells. One of these emerging lines aims to face the problem of uncertainty that exists in the generation of energy in photovoltaic installations. In this paper, we proposed to use machine learning methods to predict the state (voltage) of the batteries at several days into the future. The results obtained from two recurrent neural networks such as NARX and LSTM are compared, getting good results with both. Two approaches are considered: sample-based prediction and pattern-based forecasting.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9243139,

title = {New Smart Control based on MPPT/MEPT Algorithm for Hybrid Fuel Cell Power System},

author = {J S Artal-Sevil and I Sanz-Gorrachategui and P Pastor and C Bernal-Ruiz and F J Perez-Cebolla and Antonio Bono},

doi = {10.1109/EVER48776.2020.9243139},

year  = {2020},

date = {2020-09-01},

booktitle = {2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)},

pages = {1-10},

abstract = {In this paper, a new algorithm for enhanced management of a hybrid fuel-cell system is proposed. The purpose of this algorithm, which has been called Maximum Efficiency Point Tracking algorithm (MEPT-algorithm), is to polarize the fuel cell in an optimum point maximizing its efficiency and minimizing the fuel consumption. The goal is to guarantee fast power transients in the load while the fuel cell is kept in the optimum point by the hybridization of a fuel cell with an energy storage system (ESS) based on ultracapacitors. The hybrid power system model has been simulated in Matlab/Simulink applying the proposed algorithm and the classical Maximum Power Point Tracking (MPPT) algorithm. The combined control in DC/DC converters allows us to modify the Fuel Cell's operating point, as well as its MPPT or MEPT algorithm. A detailed analysis of the results verifies the benefits of the use of MEPT vs only the MPPT. Typical figures of merit and conclusions are also presented in this paper.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9163711,

title = {Design of a Fuzzy-Controller for a Magnetic Levitation System using Hall-Effect sensors},

author = {J S Artal-Sevil and C Bernal-Ruiz and Antonio Bono and Santos M Peñas},

doi = {10.1109/TAEE46915.2020.9163711},

year  = {2020},

date = {2020-07-01},

booktitle = {2020 XIV Technologies Applied to Electronics Teaching Conference (TAEE)},

pages = {1-9},

abstract = {This paper shows the implementation of Fuzzy Control techniques on a small Magnetic Levitation system. The analyzed application is a study problem of a non-linear and unstable system. Fuzzy control is an appropriate alternative for those cases where modelling the system is complicated, mainly due to the mathematical complexity of the model. The advantage of Fuzzy techniques is that any additional adjustment in the system only requires modifying the different fuzzy rules implemented, instead of redesigning the entire associated controller again. The control implemented here is made up of two feedback loops (position and current variables). A Hall sensor has been used to determine the position of the sphere to be levitated. Matlab/Simulink has been the software used for the development of the model and its simulation. In this way, the dynamic response of the system has been studied. The results and the different figures of merit obtained are shown by simulating the model presented. The initial objectives have been satisfactorily achieved.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{8926907,

title = {Analysis of Li-ion battery degradation using self-organizing maps},

author = {Pablo Pastor-Flores and Carlos Bernal-Ruiz and Iván Sanz-Gorrachategui and Antonio Bono and Bonifacio Martín del Brío and Jesús Sergio Artal-Sevil and Francisco J Perez-Cebolla},

doi = {10.1109/IECON.2019.8926907},

issn = {2577-1647},

year  = {2019},

date = {2019-10-01},

booktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},

volume = {1},

pages = {4525-4530},

abstract = {This paper proposes a new methodology to identify the different degradation processes of Li-Ion battery cells. The goal of this study is to determine if different degradation factors can be separated by waveform analysis from aged cells with similar remaining capacity. In contrast to other works, the proposed method identifies the past operating conditions in the cell, regardless of the actual State of Health. The methodology is based on a data-driven approach by using a SOM (Self-organizing map), an unsupervised neural network. To verify the hypothesis a SOM has been trained with laboratory data from whole data cycles, to classify cells concerning their degradation path and according to their discharge voltage patterns. Additionally, this new methodology based on the SOM allows discriminating groups of cells with different cycling conditions (based on depth of discharge, ambient temperature and discharge current). This research line is very promising for classification of used cells, not only depending on their current static parameters (capacity, impedance), but also the battery use in their past life. This will allow making predictions of the Remaining Useful Life (RUL) of a battery with greater precision.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sanchez2018adaptacion,

title = {Adaptación de las prácticas de la asignatura de Instrumentación Electrónica a la modalidad semipresencial},

author = {Carlos Medrano Sánchez and Antonio Bono and Raúl Igual Catalán and Bonifacio Martín del Brío and Inmaculada Plaza García},

year  = {2018},

date = {2018-01-01},

booktitle = {Tecnología, Aprendizaje y Enseñanza de la Electrónica: Actas del XIII Congreso de Tecnología, Aprendizaje y Enseñanza de la Electrónica, Tenerife, 20-22 de junio, 2018},

pages = {548--555},

organization = {Universidad de La Laguna},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}