文献
J-GLOBAL ID:201802234358368461
整理番号:18A1616277
複数の健康指標と極端学習機械を用いた新しい電池状態のオンライン推定法【JST・京大機械翻訳】
Novel battery state-of-health online estimation method using multiple health indicators and an extreme learning machine
著者 (7件):
Pan Haihong
(Department of Mechatronics Engineering, College of Mechanical Engineering, Guangxi University, Nanning, 530000, China)
,
Lue Zhiqiang
(State Key Laboratory of Structural Analysis for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian, 116000, China)
,
Wang Huimin
(Department of Mechatronics Engineering, College of Mechanical Engineering, Guangxi University, Nanning, 530000, China)
,
Wei Haiyan
(Department of Mechatronics Engineering, College of Mechanical Engineering, Guangxi University, Nanning, 530000, China)
,
Chen Lin
(Department of Mechatronics Engineering, College of Mechanical Engineering, Guangxi University, Nanning, 530000, China)
,
Chen Lin
(Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology, College of Mechanical Engineering, Guangxi University, Nanning, 530000, China)
,
Chen Lin
(Guangxi Key Laboratory for Electrochemical Energy Materials, Guangxi University, Nanning, 530000, China)
資料名:
Energy
(Energy)
巻:
160
ページ:
466-477
発行年:
2018年
JST資料番号:
H0631A
ISSN:
0360-5442
CODEN:
ENEYDS
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)