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Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture.
Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang.
Affiliation
  • Li L; Province-ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, 300130, China.
  • Wang P; College of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung, 41170, Taiwan.
  • Chao KH; Province-ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, 300130, China.
  • Zhou Y; College of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung, 41170, Taiwan.
  • Xie Y; School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, 300130, China.
PLoS One ; 11(9): e0163004, 2016.
Article in En | MEDLINE | ID: mdl-27632176
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Electric Power Supplies / Lithium / Models, Theoretical Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2016 Document type: Article Affiliation country: China
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Electric Power Supplies / Lithium / Models, Theoretical Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2016 Document type: Article Affiliation country: China