z-logo
open-access-imgOpen Access
Fault diagnosis for lithium-ion batteries in electric vehicles based on signal decomposition and two-dimensional feature clustering
Author(s) -
Shuowei Li,
Caiping Zhang,
Jingcai Du,
Xinwei Cong,
Linjing Zhang,
Yan Jiang,
Le Yi Wang
Publication year - 2022
Publication title -
green energy and intelligent transportation
Language(s) - English
Resource type - Journals
ISSN - 2773-1537
DOI - 10.1016/j.geits.2022.100009
Subject(s) - cluster analysis , computer science , dbscan , reliability (semiconductor) , battery pack , voltage , fault (geology) , battery (electricity) , pattern recognition (psychology) , real time computing , engineering , artificial intelligence , fuzzy clustering , electrical engineering , cure data clustering algorithm , power (physics) , physics , quantum mechanics , seismology , geology

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom