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Trends and Prospects in Fuel Cell Towards Industrialization

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: 15 July 2025 | Viewed by 880

Special Issue Editors

School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China
Interests: fuel cell water management; multiscale simulation; nonlinear control and health diagnosis
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Guest Editor
School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Interests: PEM fuel cells and electrolyzers; involving state-of-health diagnosis and protection; aging mechanisms and durability; wide-temperature-zone application

Special Issue Information

Dear Colleagues,

Fuel cells, especially proton exchange membrane fuel cells, are moving towards industrialization. After several decades of development, the durability, reliability, and low-cost material design still represent challenges. The main limitation is our unclear knowledge of reactant behaviours at three-phase boundaries, the macroscopic preparation of low-cost materials coupled with poor performance, and high-efficiency optimization and control of systems. This Special Issue focuses on new technologies of fuel cells and we encourage researchers to submit papers on the following topics:  electrochemical reaction investigation and characterization, precious-group-metal-free catalysts and low loading PGM catalyst design, high-efficiency mass and electron transfer, system design, optimization, and optimal control. We welcome submissions that display originality in the form of research papers, reviews, and other corresponding forms.

Dr. Yuehua Li
Dr. Peng Ren
Guest Editors

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Keywords

  • fuel cell
  • material optimization
  • mass transfer
  • system control

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Published Papers (1 paper)

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Research

22 pages, 7361 KiB  
Article
Exploring Performance Degradation of Proton Exchange Membrane Fuel Cells Based on Diffusion Transformer Model
by Lingling Lv, Pucheng Pei, Peng Ren, He Wang and Geng Wang
Energies 2025, 18(5), 1191; https://doi.org/10.3390/en18051191 - 28 Feb 2025
Viewed by 480
Abstract
Proton exchange membrane fuel cells (PEMFCs) stand at the forefront of energy conversion technology, efficiently converting the chemical energy of hydrogen and oxygen directly into electricity. Research on predicting the remaining useful life of PEMFCs has long been a focus, as it plays [...] Read more.
Proton exchange membrane fuel cells (PEMFCs) stand at the forefront of energy conversion technology, efficiently converting the chemical energy of hydrogen and oxygen directly into electricity. Research on predicting the remaining useful life of PEMFCs has long been a focus, as it plays a crucial role in preventing failures and mitigating safety risks. This paper introduces a robust diffusion transformer (DiT) model, which is a novel approach leveraging generative artificial intelligence (GAI) technology to innovate the existing methods for predicting the performance degradation of PEMFCs. This model employs random Gaussian noise to generate stable performance degradation data of PEMFCs under specified conditions. The predictive accuracy is then assessed by benchmarking against a bi-directional long short-term memory recurrent neural network (Bi-LSTM) using two distinct experimental datasets. The evaluation shows that the DiT model achieves higher predictive accuracy than the reference model. Specifically, the mean absolute prediction error is reduced by 72.7% under steady-state conditions and 59.3% under dynamic conditions. Correspondingly, the remaining useful life error (RE) is diminished by 80% and 88%, respectively. These findings indicate that the DiT model has significant potential in PEMFCs performance degradation research. Full article
(This article belongs to the Special Issue Trends and Prospects in Fuel Cell Towards Industrialization)
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