Work

PID-NN: A Dual-Branch Neural Network With Physics-Informed Constraints for State-of-Health Estimation of Lithium-Ion Batteries

Year: 2025

Type: article

Source: IEEE Transactions on Transportation Electrification

DOI: 10.1109/tte.2025.3645831

Authors: Caiwen Gan, Ronglei Gui, Xudong Lv, Zhekang Dong, Mingyu Gao

Institution: Hangzhou Dianzi University

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 Key Scientific Instrument and Equipment Development Projects of China

Award: G2737163643

OpenAlex ID: W4417469999

FWCI: 0.253

Cites: 41

Cited by: 1

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