Title : ( Estimating the Capacity and RUL of LIBs using an artificial neural network )
Authors: Mohammad Javad Tavakkoli Heravi , Mahdi Arya khah , Elham Yasari ,
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Abstract
The capacity and remaining usable life (RUL) of four different types of lithium-ion batteries (LIBs) manufactured by this organization—the B0005, B0006, B0007, and B0018—were calculated in this study using data released by NASA. Both a neural network with one input variable (cycle number) and a neural network with five input variables (cycle number, voltage, temperature, current, and time) were used in this investigation. The battery capacity is regarded as the output variable in both situations. The neural network with five input variables has a more accurate estimation of the batteries\\\\\\\\\\\\\\\' capacity and RUL, according to the results.
Keywords
, lithium-ion battery, remaining useful life, capacity, neural network.
@inproceedings{paperid:1103227,
author = {Tavakkoli Heravi, Mohammad Javad and Arya Khah, Mahdi and Elham Yasari, },
title = {Estimating the Capacity and RUL of LIBs using an artificial neural network},
booktitle = {Estimating the Capacity and RUL of LIBs using an artificial neural network},
year = {2025},
location = {IRAN},
keywords = {lithium-ion battery; remaining useful life; capacity; neural network.},
}
%0 Conference Proceedings
%T Estimating the Capacity and RUL of LIBs using an artificial neural network
%A Tavakkoli Heravi, Mohammad Javad
%A Arya Khah, Mahdi
%A Elham Yasari,
%J Estimating the Capacity and RUL of LIBs using an artificial neural network
%D 2025
