Title :
Storage device unit modeling
Author_Institution :
Dept. of Eng. Sci., Suez Univ., Suez, Egypt
Abstract :
This paper proposes storage device unit (Lead acid battery) model as one of various batteries commercially available for meeting the storage needs. To help designers, researchers and users in pointing the direction for indigenous research in electricity storage technologies. The parameters of the battery model are identified depending on curve fitting with the aid of improved Thevenin battery model, and the model is validated with a 12 V, 4Ah lead-acid battery Yuasa NP4-12 Battery. The discharge and charge characteristics are studied using this model. The model parameters and characteristics are well depicted in the form of 3D figures as the training data for ANN models. Then Artificial Neural Network (ANN) technique models are adopted to generalize parameters estimation process for the whole capacity rates range due to its advantages. ANN models are created with suitable numbers of layers and neurons, which trained, simulated, checked and their algebraic equations are concluded accurately with excellent regression constant for both 1, 0.99997.
Keywords :
curve fitting; electrical engineering computing; neural nets; parameter estimation; secondary cells; ANN models; Li; Yuasa NP4-12 battery; algebraic equations; artificial neural network technique; charge characteristics; curve fitting; discharge characteristics; electricity storage technology; improved Thevenin battery model; lead acid battery model; parameter estimation process; storage device unit modeling; voltage 12 V; Discharges (electric); Equations; Lead; Mathematical model; Lead-acid battery; and estimation; model; neural network; storage;
Conference_Titel :
Engineering and Technology (ICET), 2014 International Conference on
Conference_Location :
Cairo
DOI :
10.1109/ICEngTechnol.2014.7016809