Compact Neural Modeling of Single Flow Zinc-Nickel Batteries Based on Jaya Optimization
文献类型：会议论文
| 作者 | L. Zhang; K. Li; Z. Yang; X. Li; Y. Guo; D. Du; C. Wong |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 会议地点 | 里约 |
| 英文摘要 | As a novel family member of redox flow batteries (RFBs), the single flow zinc–nickel battery (ZNB) without ion exchange membranes has been popular in recent years due to the high charging and discharging efficiencies. The electrical behaviour is the key to the battery management system in particularly regarding the estimation of the battery state-of charge (SOC). Unlike the electrochemical mechanism models and equivalent circuit models, the neural network based black box model ignores the electrochemical reactions and is promising to be adopted in the ZNB battery modelling. In this paper, a novel compact radial basis function neural network is proposed using a two-stage layer selection strategy to determine the network structure. During this procedure, Jaya optimization is utilized to determine the non-linear parameters in the selected hidden node of RBF neural network (RBF-NN), establishing TSS\_Jaya\_RBF model. The method is implemented on modelling ZNB to capture the non-linear behaviours through the readily measurable input signals. Experimental results manifest the accurate estimation abilities and confirm the effectiveness of the proposed approach. |
| 语种 | 英语 |
| URL标识 | 查看原文 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14075]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 推荐引用方式 GB/T 7714 | L. Zhang,K. Li,Z. Yang,et al. Compact Neural Modeling of Single Flow Zinc-Nickel Batteries Based on Jaya Optimization[C]. 见:. 里约. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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