Compact Neural Modeling of Single Flow Zinc-Nickel Batteries Based on Jaya Optimization
Zhang L.2; Li K.1; Yang Z.4; Li X.1; Guo Y.4; Du D.2; Wong C.3
Source Publication2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
AbstractAs a novel family member of the redox flow batteries (RFBs), the single flow zincnickel battery (ZNB) without ion exchange membranes has attracted a lot of interests in recent years due to the high charging and discharging efficiencies. To understand the electrical behaviour is a key for proper battery management system. Unlike the electrochemical mechanism models and equivalent circuit models, the neural network based black-box model does not need knowledge about the electrochemical reactions and is a promising and adaptive approach for the ZNB battery modelling. In this paper, a compact radial basis function neural network is developed using a two-stage layer selection strategy to determine the network structure. While Jaya optimization is utilized to determine the non-linear parameters in the selected hidden nodes of the resultant RBF neural network (RBF-NN) model. The proposed method is implemented to model the ZNB to capture the non-linear electric behaviours through the readily measurable input signals. Experimental results manifest the accurate prediction capability of the resultant neural model and confirm the effectiveness of the proposed approach.
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Queen's University Belfast
2.Shanghai University
3.Universidade de Macau
4.Shenzhen Institute of Advanced Technology
Recommended Citation
GB/T 7714
Zhang L.,Li K.,Yang Z.,et al. Compact Neural Modeling of Single Flow Zinc-Nickel Batteries Based on Jaya Optimization[C],2018.
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