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Trends and Prospects in Fuel Cell Towards Industrialization
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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 1730

Special Issue Editors

Dr. Yuehua Li

E-Mail Website
Guest Editor
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China
Interests: fuel cell water management; multiscale simulation; nonlinear control and health diagnosis
Special Issues, Collections and Topics in MDPI journals
Dr. Peng Ren

E-Mail Website
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

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

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Published Papers (3 papers)

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Research

17 pages, 3645 KiB  
Article
A Multi-Objective Temperature Control Method for a Multi-Stack Fuel Cell System with Different Stacks Based on Model Predictive Control
by Wei Shen, Hongtao Su, Jianhua Gao, Lei Fan, Gang Zhang and Su Zhou
Energies 2025, 18(10), 2443; https://doi.org/10.3390/en18102443 - 9 May 2025
Viewed by 266
Abstract
The multi-stack fuel cell system (MFCS) has advantages such as a wide range, long life, and high efficiency; however, its multiple heat sources impose higher requirements on the thermal management system, especially for different stacks. In order to control each stack temperature in [...] Read more.
The multi-stack fuel cell system (MFCS) has advantages such as a wide range, long life, and high efficiency; however, its multiple heat sources impose higher requirements on the thermal management system, especially for different stacks. In order to control each stack temperature in an MFCS, the model predictive control (MPC) algorithm based on the backpropagation (BP) neural network is proposed. Firstly, dynamic characteristics have been obtained experimentally for selected PEMFC stacks of different powers. Based on experimental data, a parallel multi-stack fuel cell thermal management subsystem with different stack powers model is established and a system prediction model of the BP neural network is trained by applying the MFCS thermal management subsystem model simulation data. Then, the step response matrix of the system prediction model is obtained at typical operating conditions, and a dynamic matrix controller (DMC) is designed. Finally, a test operating condition is designed for simulation analysis. The results show that the DMC based on BP neural network can quickly and accurately control each stack temperature of the MFCS, while having the characteristics of small overshoot and short regulation time. Full article
(This article belongs to the Special Issue Trends and Prospects in Fuel Cell Towards Industrialization)
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23 pages, 5711 KiB  
Article
A Control Framework for the Proton Exchange Membrane Fuel Cell System Integrated the Degradation Information
by Lei Fan, Jianhua Gao, Wei Shen, Hongtao Su, Su Zhou and Yiwei Hou
Energies 2025, 18(10), 2438; https://doi.org/10.3390/en18102438 - 9 May 2025
Viewed by 247
Abstract
To solve the control problem of the performance degradation of proton exchange membrane fuel cells (PEMFCs), a novel control framework based on the performance degradation is proposed. This control framework introduces the results of the state of health (SoH) estimation and remaining useful [...] Read more.
To solve the control problem of the performance degradation of proton exchange membrane fuel cells (PEMFCs), a novel control framework based on the performance degradation is proposed. This control framework introduces the results of the state of health (SoH) estimation and remaining useful lifetime (RUL) prediction, which were used for the controller design because they determine the PEMFC output power. Furthermore, the information of SoH and RUL could be reflected the PEMFC health state and provided maintenance recommendations. The desired power of the stack was obtained, which was used as the real-time desired power of the PEMFC system by synthesizing the RUL, SoH, and ECU information of the stack. The results showed that when the PEMFC system used the designed control framework, the RUL and SoH information could be provided. The stack temperature showed an increasing and then decreasing trend, which indicates that the stack temperature was still controllable by controlling the speeds of the pump and fan. Full article
(This article belongs to the Special Issue Trends and Prospects in Fuel Cell Towards Industrialization)
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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
Cited by 1 | Viewed by 748
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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