107451 20240122154814.0 doi 10.3390/electronics10182294 sideral 124882 ART-2021-124882 eng Pastor-Flores, Pablo (orcid)0000-0002-7897-3596 Unsupervised Neural Networks for Identification of Aging Conditions in Li-Ion Batteries 2021 Access copy available to the general public Unrestricted This paper explores a new methodology based on data-driven approaches to identify and track degradation processes in Li-ion batteries. Our goal is to study if it is possible to differentiate the state of degradation of cells that present similar aging in terms of overall parameters (similar remaining capacity, state of health or internal resistance), but that have had different applications or conditions of use (different discharge currents, depth of discharges, temperatures, etc.). For this purpose, this study proposed to analyze voltage waveforms of cells obtained in cycling tests by using an unsupervised neural network, the Self-Organizing Map (SOM). In this work, a laboratory dataset of real Li-ion cells was used, and the SOM algorithm processed battery cell features, thus carrying out smart sensing of the battery. It was shown that our methodology differentiates the previous conditions of use (history) of a cell, complementing conventional metrics such as the state of health, which could be useful for the growing second-life market because it allows for determining more precisely the state of disease of a battery and assesses its suitability for a specific application. info:eu-repo/grantAgreement/ES/FEDER/CDTI/MIR-20201042 CARDHIN info:eu-repo/grantAgreement/ES/MINECO-FEDER/TIN2017-88841-R info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.69 2021 COMPUTER SCIENCE, INFORMATION SYSTEMS 100 / 163 = 0.613 2021 Q3 T2 PHYSICS, APPLIED 82 / 161 = 0.509 2021 Q3 T2 ENGINEERING, ELECTRICAL & ELECTRONIC 139 / 274 = 0.507 2021 Q3 T2 0.59 2021 Computer Networks and Communications 2021 Q2 Signal Processing 2021 Q2 Hardware and Architecture 2021 Q2 Control and Systems Engineering 2021 Q2 3.7 2021 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Martín-del-Brío, Bonifacio Universidad de Zaragoza (orcid)0000-0002-3643-2847 Bono-Nuez, Antonio Universidad de Zaragoza (orcid)0000-0001-5664-7063 Sanz-Gorrachategui, Iván Universidad de Zaragoza (orcid)0000-0003-0198-5094 Bernal-Ruiz, Carlos Universidad de Zaragoza (orcid)0000-0001-9334-4870 5008 785 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Tecnología Electrónica 10, 18 (2021), 2294 [20 pp] Electronics (Basel) Electronics 2079-9292 3584565 http://zaguan.unizar.es/record/107451/files/texto_completo.pdf Versión publicada 2766126 http://zaguan.unizar.es/record/107451/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:107451 articulos driver 2024-01-22-15:33:21 ARTICLE