GIEC OpenIR
A Novel Pigeon-Inspired Optimized RBF Model for Parallel Battery Branch Forecasting
Zhang, Yanhui1,2,3,4; Lin, Shili5; Ma, Haiping6; Guo, Yuanjun1,2,3,4; Feng, Wei1,2,3,4,7,8
2021-02-23
发表期刊COMPLEXITY
ISSN1076-2787
卷号2021页码:7
通讯作者Guo, Yuanjun(yj.guo@siat.ac.cn) ; Feng, Wei(wei.feng@siat.ac.cn)
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.
DOI10.1155/2021/8895496
收录类别SCI
语种英语
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
项目资助者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
WOS类目Mathematics, Interdisciplinary Applications ; Multidisciplinary Sciences
WOS记录号WOS:000627396800006
出版者WILEY-HINDAWI
引用统计
文献类型期刊论文
条目标识符http://ir.giec.ac.cn/handle/344007/32895
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.Shenzhen Inst Adv Technol, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen, Peoples R China
2.Chinese Acad Sci, Shenzhen Inst Adv Technol, Guangdong Prov Key Lab Robot & Intelligent Syst, Beijing, Peoples R China
3.Ultrason Nondestruct Engn Technol Res Ctr Guangdo, Shenzhen 518055, Peoples R China
4.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
5.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China
6.Shaoxing Univ, Dept Elect Engn, Shaoxing 312000, Peoples R China
7.Univ Chinese Acad Sci, Beijing 100000, Peoples R China
8.Chinese Univ Hong Kong, Dept Mech & Automat Engn, Shatin, Hong Kong, 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.
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