Work

State of Health and Remaining Useful Life Prediction for Lithium-Ion and Sodium-Ion Batteries Based on Segmental Incremental Capacity Features

Year: 2026

Type: article

Source: ACS Applied Energy Materials

DOI: 10.1021/acsaem.6c01374

Authors: Hong Qian, Zhong Tang, Yuhao Liu, Xiangyang Liu, Haoyang Cui

Institution: Shanghai University of Electric Power

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

Funder: National Natural Science Foundation of China

Award: G1011481481

OpenAlex ID: W7166702162

FWCI:

Cites: 41

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