A data-driven method with sample entropy and CEEMDAN for short-term performance degradation prediction of dynamic hydrogen fuel cells-Reference-Cited by-同舟云学术

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A data-driven method with sample entropy and CEEMDAN for short-term performance degradation prediction of dynamic hydrogen fuel cells

Published:2024-09 Issue: Volume:83 Page:916-932
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Cui Siyuan,Jia Jianfang^ORCID,Pang Xiaoqiong,Wen Jie,Shi Yuanhao,Zeng Jianchao

Publisher

Elsevier BV

Reference46 articles.

1. Online extremum seeking-based optimized energy management strategy for hybrid electric tram considering fuel cell degradation;Li;Appl Energy,2021

2. Multiobjective optimization and data-driven constraint adaptive predictive control for efficient and stable operation of PEMFC system;Li;IEEE Trans Ind Electron,2020

3. Design of durability test protocol for vehicular fuel cell systems operated in power-follow mode based on statistical results of on-road data;Xu;J Power Sources,2018

4. Approaches to avoid flooding in association with pressure drop in proton exchange membrane fuel cells;Li;Appl Energy,2018

5. Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data‐driven approaches;Mao;Fuel Cell,2017

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