Transferable data-driven capacity estimation for lithium-ion batteries with deep learning: A case study from laboratory to field applications-Reference-Cited by-同舟云学术

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Transferable data-driven capacity estimation for lithium-ion batteries with deep learning: A case study from laboratory to field applications

Published:2023-11 Issue: Volume:350 Page:121747
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Wang Qiao,Ye Min,Cai Xue,Sauer Dirk Uwe,Li Weihan

Funder

Bundesministerium für Bildung und Forschung

China Scholarship Council

Fundamental Research Funds for the Central Universities

Shanxi Provincial Key Research and Development Project

Shaanxi Province Key Research and Development Projects

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference50 articles.

1. Evaporation-induced sintering of liquid metal droplets with biological nanofibrils for flexible conductivity and responsive actuation;Li;Nat Commun,2019

2. Combined economic and technological evaluation of battery energy storage for grid applications;Davies;Nat Energy,2019

3. Battery lifetime prognostics;Hu;Joule,2019

4. Rapidly falling costs of battery packs for electric vehicles;Nykvist;Nat Clim Chang,2015

5. Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: recent advances and perspectives;Xiong;Renew Sustain Energy Rev,2020

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