A novel data-driven fast capacity estimation of spent electric vehicle lithium-ion batteries

Energies

Volumn 7, Issue 12, 2014, Pages 8076-8094

  Zhang, Caiping ^a   Jiang, Jiuchun ^a   Zhang, Weige ^a   Wang, Yukun ^a   Sharkh, Suleiman M ^b   Xiong, Rui ^c  

^a BEIJING JIAOTONG UNIVERSITY   (China)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c BEIJING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Artificial neural networks; Fast capacity estimation; Lithium ion batteries; Robustness; Second life

Indexed keywords

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; DISTURBANCE REJECTION; ELECTRIC BATTERIES; ELECTRIC VEHICLES; IONS; LITHIUM; LITHIUM ALLOYS; LITHIUM COMPOUNDS; LITHIUM-ION BATTERIES; NEURAL NETWORKS; ROBUSTNESS (CONTROL SYSTEMS); SECONDARY BATTERIES; UNCERTAINTY ANALYSIS;

CAPACITY ESTIMATION; IDENTIFICATION APPROACH; LARGE-SCALE APPLICATIONS; LAW OF LARGE NUMBERS; PARAMETER MEASUREMENT; REGRESSION COEFFICIENT; SECOND LIFE; THREE LAYER BACK PROPAGATION ARTIFICIAL NEURAL NETWORK;

LITHIUM BATTERIES;

EID: 84921359178     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en7128076     Document Type: Article

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