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contributor authorLi, Cong
contributor authorPan, Rui
contributor authorSi, Ruibin
contributor authorLiu, Quanfeng
contributor authorZhou, Juan
date accessioned2026-08-20T11:18:09Z
date available2026-08-20T11:18:09Z
date copyright2025/12/26
date issued2026
identifier otherJLEED9.EYENG-6176.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311997
description abstractAbstractAccurate estimation of the state of health (SOH) of lithium-ion batteries is a critical prerequisite for ensuring their safe and stable operation. However, the complex operating environments in practical applications often result in raw data ...
publisherAmerican Society of Civil Engineers
titleState of Health Estimation for Lithium-Ion Batteries Using Multiple Indirect Feature Extraction and Bayesian Optimization–Transformer Model
typeJournal Article
journal volume152
journal issue2
journal titleJournal of Energy Engineering
identifier doi10.1061/JLEED9.EYENG-6176
journal fristpage04025118-1
journal lastpage04025118-11
page11
treeJournal of Energy Engineering:;2026:;Volume ( 152 ):;issue: 002
contenttypeFulltext


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