Modelling of Ultracapacitors Using Recurrent Artificial Neural Network
Adrian Chmielewski , Jakub Możaryn , Piotr Piórkowski , Robert Gumiński , Krzysztof Jakub Bogdziński
AbstractThis article presents an artificial neural network (ANN) model of the ultracapacitors based on experimental data acquired from laboratory purposely built test stand for dynamic load cycle tests. Because of a nonlinear description of discharging dynamics in subsequent cycles and a coupling of the terminal voltage and temperatures of a ultracapacitor, the recurrent artificial neural network structure (R-ANN) structure is proposed. As a result, it was presented the accuracy analysis based on the statistical quality indices of proposed modeling approach.
|Publication size in sheets||0.5|
|Book||Szewczyk Roman, Zieliński Cezary, Kaliczyńska Małgorzata (eds.): Automation 2018: Advances in Automation, Robotics and Measurement Techniques, Advances in Intelligent Systems and Computing, vol. 743, 2018, Springer International Publishing, ISBN 978-3-319-77178-6, [978-3-319-77179-3], 795 p., DOI:10.1007/978-3-319-77179-3|
|Keywords in English||ultracapacitor, test stand, artificial neural networks, recurrent artificial neural network|
|License||Publisher website (books and chapters only); published final; ; after publication|
|Score||= 20.0, 20-10-2019, ChapterFromConference|
|Publication indicators||= 2|
|Citation count*||7 (2019-11-25)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.