Approximation of Battery Transfer Function Using Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137696" target="_blank" >RIV/00216305:26220/20:PU137696 - isvavai.cz</a>
Result on the web
<a href="https://iopscience.iop.org/article/10.1149/09901.0351ecst" target="_blank" >https://iopscience.iop.org/article/10.1149/09901.0351ecst</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1149/09901.0351ecst" target="_blank" >10.1149/09901.0351ecst</a>
Alternative languages
Result language
angličtina
Original language name
Approximation of Battery Transfer Function Using Neural Network
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/LO1210" target="_blank" >LO1210: Energy for Sustainable Development</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ECS
ISBN
978-80-214-5889-5
ISSN
1938-5862
e-ISSN
1938-6737
Number of pages
6
Pages from-to
351-356
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Brno
Event date
Sep 6, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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