Work

Hybrid neural network and dynamic decay model for life prediction of solid oxide fuel cell combined heat and power systems

Year: 2025

Type: article

Source: Journal of Power Sources

DOI: 10.1016/j.jpowsour.2025.237165

Authors: Yazhou Shi, Hongxiang Zheng, Wenchun Jiang, Ming Song, Yun Luo, Xiucheng Zhang, Shan-Tung Tu

Institutions: China University of Petroleum, East China, State Key Laboratory of Heavy Oil, East China University of Science and Technology

Language: English

Topic: Advancements in Solid Oxide Fuel Cells

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

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

Open Access status: closed

Funders: China University of Petroleum, Beijing, China National Funds for Distinguished Young Scientists, National High-tech Research and Development Program, National Key Research and Development Program of China

Awards: G1732440598, G8744695515, G8787103619

OpenAlex ID: W4409904679

FWCI: 1.488

Cites: 34

Cited by: 7

Related to: 10