Knowledge Management System Of Guangzhou Institute of Energy Conversion, CAS
| 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 | |
| Source Publication | COMPLEXITY
 |
| ISSN | 1076-2787 |
| Volume | 2021Pages:7 |
| Corresponding Author | Guo, Yuanjun(yj.guo@siat.ac.cn) ; Feng, Wei(wei.feng@siat.ac.cn) |
| Abstract | 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. |
| DOI | 10.1155/2021/8895496 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 Research Area | Mathematics ; Science & Technology - Other Topics |
| Funding Organization | 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 Subject | Mathematics, Interdisciplinary Applications ; Multidisciplinary Sciences |
| WOS ID | WOS:000627396800006 |
| Publisher | WILEY-HINDAWI |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.giec.ac.cn/handle/344007/32895 |
| Collection | 中国科学院广州能源研究所 |
| Corresponding Author | Guo, Yuanjun; Feng, Wei |
| Affiliation | 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 |
| Recommended Citation 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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