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CIPÍN, R.; TOMAN, M.; PROCHÁZKA, P.; PAZDERA, I.
Original Title
Estimation of Depth of Discharge of Li-ion Battery Using Neural Network
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
This paper deals with the estimation of depth of discharge for Li-ion batteries. Estimation is based on the knowledge of discharging curves measured for discrete values of loading currents. The estimator of the depth of discharge is a form of feedforward neural network which is trained with the measured data of discharge curves. Accuracy of estimation of the depth of discharge is shown for arbitrary generated and measured loading characteristics, where the depth of discharge is estimated by the designed neural network and measured by using the Coulomb counting method.
English abstract
Keywords
Estimation; Li-ion, neural network
Key words in English
Authors
RIV year
2022
Released
08.12.2021
Book
ECS
ISBN
1938-5862
Periodical
ECS Transactions
Volume
151
Number
1
State
United States of America
Pages from
541
Pages to
547
Pages count
7
URL
https://iopscience.iop.org/article/10.1149/10501.0541ecst
BibTex
@inproceedings{BUT173089, author="Radoslav {Cipín} and Marek {Toman} and Petr {Procházka} and Ivo {Pazdera}", title="Estimation of Depth of Discharge of Li-ion Battery Using Neural Network", booktitle="ECS", year="2021", journal="ECS Transactions", volume="151", number="1", pages="541--547", doi="10.1149/10501.0541ecst", issn="1938-5862", url="https://iopscience.iop.org/article/10.1149/10501.0541ecst" }