Experimental Evaluation of Mathematical and Artificial Neural Network Modeling of Energy Storage System
Adrian Chmielewski , Jakub Możaryn , Robert Gumiński , Krzysztof Jakub Bogdziński , Przemysław Szulim
AbstractThis article presents an experimental evaluation based on a mathematical model and an artificial neural network (ANN) model of an energy storage system. Because of a nonlinear description of charging/discharging dynamics in subsequent cycles and a coupling of the terminal voltage and temperatures of a battery, the recurrent artificial neural network structure (R-ANN) is proposed. Both models, analytical and R-ANN were employed to predict a behavior of the VRLA AGM battery. A training and testing data were gathered at the laboratory stand in different working conditions. As a result, we present the analysis of differences between proposed modeling approaches.
|Publication size in sheets||0.65|
|Book||Awrejcewicz Jan (eds.): Dynamical Systems in Applications, Springer Proceedings in Mathematics & Statistics, vol. 249, 2018, Springer, ISBN 978-3-319-96600-7, [978-3-319-96601-4], 506 p., DOI:10.1007/978-3-319-96601-4|
|Keywords in English||recurrent artificial neural network, energy storage, experimental evaluation, VRLA AGM battery|
|License||Publisher website (books and chapters only); published final; ; after publication|
|Score||= 20.0, 16-01-2020, ChapterFromConference|
|Publication indicators||= 1|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.