Open AccessDevelopment of a voltage curve prediction model for lithium-ion battery based on destructive tests
Author(s) -
RAFAEL SAADI DANTAS TEIXEIRA,
Daniel Ramos Louzada,
L. A.P. Gusmão,
Rodrigo Flora Calili
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1826/1/012091
Subject(s) - battery (electricity) , voltage , power (physics) , artificial neural network , lithium ion battery , work (physics) , computer science , lithium (medication) , energy density , reliability engineering , electrical engineering , automotive engineering , engineering , artificial intelligence , engineering physics , mechanical engineering , physics , medicine , quantum mechanics , endocrinology
With the increasing development of portable devices, research on mobile power sources have been an important goal. Thus, the improvement on their safety, energy density and degradation rate is the current challenge of different researchers. The present work seeks to develop an algorithm, based on artificial neural networks, to predict the voltage curve of a lithium-ion battery based on destructive tests. It was found that the developed system can define the condition of the battery in the test and generates voltage curves that allow the estimation of the batterys charge and its charging time.