A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting

doi:10.1155/2021/8895496

	A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting
	Zhang, Yanhui 1,2,3,5; Lin, Shili 4; Ma, Haiping 8; Guo, Yuanjun 1,2,3,5; Feng, Wei 1,2,3,5,6,7
刊名	COMPLEXITY
	2021-02-23
卷号	2021 页码:7
ISSN号	1076-2787
DOI	10.1155/2021/8895496
通讯作者	Guo, Yuanjun(yj.guo@siat.ac.cn) ; Feng, Wei(wei.feng@siat.ac.cn)
英文摘要	Battery energy storage is the pivotal project of renewable energy systems reform and an effective regulator of energy flow. Parallel battery packs can effectively increase the capacity of battery modules. However, the power loss caused by the uncertainty of parallel battery branch current poses severe challenge to the economy and safety of electric vehicles. Accuracy of battery branch current prediction is needed to improve the parallel connection. This paper proposes a radial basis function neural network model based on the pigeon-inspired optimization method and successfully applies the algorithm to predict the parallel branch current of the battery pack. Numerical results demonstrate the high accuracy of the proposed pigeon-inspired optimized RBF model for parallel battery branch forecasting and provide a useful tool for the prediction of parallel branch currents of battery packs.
资助项目	Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems[2019B121205007] ; Science and Technology Innovation Commission of Shenzhen[ZDSYS20190902093209795] ; Science and Technology Innovation Commission of Shenzhen[JCYJ20170818153048647] ; Science and Technology Innovation Commission of Shenzhen[JCYJ20180507182239617] ; Science and Technology Innovation Commission of Shenzhen[JCYJ2018050718223961] ; National Natural Science Foundation of China[U1813222] ; National Natural Science Foundation of Guangdong[2016A030313177] ; Guangdong Frontier and Key Technological Innovation[2017B090910013] ; Zhejiang Provincial Natural Science Foundation of China[LY19F030011]
WOS研究方向	Mathematics ; Science & Technology - Other Topics
语种	英语
出版者	WILEY-HINDAWI
WOS记录号	WOS:000627396800006
资助机构	Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems ; Science and Technology Innovation Commission of Shenzhen ; National Natural Science Foundation of China ; National Natural Science Foundation of Guangdong ; Guangdong Frontier and Key Technological Innovation ; Zhejiang Provincial Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.giec.ac.cn/handle/344007/32894]
专题	中国科学院广州能源研究所
通讯作者	Guo, Yuanjun; Feng, Wei
作者单位	1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China 2.Chinese Acad Sci, Shenzhen Inst Adv Technol, Guangdong Prov Key Lab Robot & Intelligent Syst, Beijing, Peoples R China 3.Shenzhen Inst Adv Technol, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen, Peoples R China 4.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China 5.Ultrason Nondestruct Engn Technol Res Ctr Guangdo, Shenzhen 518055, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100000, Peoples R China 7.Chinese Univ Hong Kong, Dept Mech & Automat Engn, Shatin, Hong Kong, Peoples R China 8.Shaoxing Univ, Dept Elect Engn, Shaoxing 312000, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yanhui,Lin, Shili,Ma, Haiping,et al. A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting[J]. COMPLEXITY,2021,2021:7.
APA	Zhang, Yanhui,Lin, Shili,Ma, Haiping,Guo, Yuanjun,&Feng, Wei.(2021).A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting.COMPLEXITY,2021,7.
MLA	Zhang, Yanhui,et al."A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting".COMPLEXITY 2021(2021):7.