Publication detail

Approximation of Battery Transfer Function Using Neural Network

CIPÍN, R. TOMAN, M. PROCHÁZKA, P. PAZDERA, I. MIKLÁŠ, J.

Original Title

Approximation of Battery Transfer Function Using Neural Network

Type

conference paper

Language

English

Original Abstract

This paper deals with a mathematical description of an alkaline battery impedance dependence on frequency. This mathematical description is done in two different ways. In the first case, a general fractional transfer function is used and in the second case an artificial neural network is used. Both approaches are discussed and compared with real measurement.

Keywords

Li-ion; model; neural network

Authors

CIPÍN, R.; TOMAN, M.; PROCHÁZKA, P.; PAZDERA, I.; MIKLÁŠ, J.

Released

11. 12. 2020

ISBN

1938-5862

Periodical

ECS Transactions

Year of study

99

Number

1

State

United States of America

Pages from

351

Pages to

356

Pages count

6

URL

https://iopscience.iop.org/article/10.1149/09901.0351ecst

BibTex

@inproceedings{BUT165875,
  author="Radoslav {Cipín} and Marek {Toman} and Petr {Procházka} and Ivo {Pazdera} and Ján {Mikláš}",
  title="Approximation of Battery Transfer Function Using Neural Network",
  booktitle="ECS",
  year="2020",
  journal="ECS Transactions",
  volume="99",
  number="1",
  pages="351--356",
  doi="10.1149/09901.0351ecst",
  issn="1938-5862",
  url="https://iopscience.iop.org/article/10.1149/09901.0351ecst"
}