Dynamic degradation identification of solid oxide fuel cell systems based on automatic spectral clustering and neighborhood rough sets
Author:
Affiliation:
1. Huazhong University of Science and Technology,Wuhan,China
2. Wuhan Huamao Automation Co., Ltd.,Wuhan,China
Funder
Technology Development
Jiangsu Provincial Key Research and Development Program
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10598401/10598402/10598737.pdf?arnumber=10598737
Reference15 articles.
1. Solid oxide fuel cell (SOFC) performance evaluation, fault diagnosis and health control: A review
2. Generalized Spatial–Temporal Fault Location Method for Solid Oxide Fuel Cells Using LSTM and Causal Inference
3. Degradation prediction of PEMFCs using stacked echo state network based on genetic algorithm optimization
4. Long term performance degradation analysis and optimization of anode supported solid oxide fuel cell stacks
5. Degradations of the electrochemical performance of solid oxide fuel cell induced by material microstructure evolutions
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