Detail publikačního výsledku

Approximation of Battery Transfer Function Using Neural Network

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

Originální název

Approximation of Battery Transfer Function Using Neural Network

Anglický název

Approximation of Battery Transfer Function Using Neural Network

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

Li-ion; model; neural network

Klíčová slova v angličtině

Li-ion; model; neural network

Autoři

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

Rok RIV

2021

Vydáno

11.12.2020

Kniha

ECS

ISSN

1938-5862

Periodikum

ECS Transactions

Svazek

99

Číslo

1

Stát

Spojené státy americké

Strany od

351

Strany do

356

Strany počet

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"
}