Work

State of Health and Remaining Useful Life Prediction of Lithium-Ion Batteries Based on a Hybrid Network

Year: 2025

Type: article

Source: Journal of Energy Engineering

DOI: 10.1061/jleed9.eyeng-6245

Authors: Chengfu Liu, Dexin Gao, Qianmiao Cheng, Qing Yang

Institutions: Qingdao University of Science and Technology, Qingdao University of Technology

Language: English

Topic: Advanced Battery Technologies Research

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W7114892872

FWCI: 1.52

Cites: 25

Cited by: 6

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