4.8 Review

IS Thermal management of polymer electrolyte membrane fuel cells: A review of cooling methods, material properties, and durability

期刊

APPLIED ENERGY
卷 286, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.116496

关键词

PEM fuel cell; Thermal management; Cooling; Material; Durability; Review

向作者/读者索取更多资源

This review summarized recent progress in thermal management of Proton Exchange Membrane (PEM) fuel cells, focusing on waste heat generation mechanisms, cooling methods, cold starts, material properties, and durability. The challenge of cooling PEM fuel cell stacks and coupling thermal and water managements is discussed, along with proposed future directions for research.
Proton exchange membrane (PEM) fuel cells are a promising electrochemical energy converter with an energy efficiency as high as 60%. Thermal management plays an important role in PEM fuel cell operation. In this review, recent progress in thermal management is summarized with in-depth discussion on the waste heat generation mechanisms, thermal analysis, non-isothermal two-phase flow, cooling methods, cold starts, and relevant material properties and durability. Due to low operating temperature (similar to 80 degrees C), cooling PEM fuel cell stacks is much more challenging than traditional combustion engines. Various cooling methods are discussed and compared, along with the cooling strategies implemented in fuel cell electric vehicles (FCEVs). A challenging subject is to couple the thermal and water managements, such as non-isothermal two-phase flow, heat pipe effect, and two-phase interface dynamics. Cold start, i.e. startup from subfreezing condition, is discussed with in-depth analysis of key parameters regarding ice formation/melt and cold-start capability. Degradation, such as delamination and electrochemical active surface area (ECSA) loss during thermal, humidity and freeze/thaw cycles, is also briefly reviewed. Future work is proposed to further advance thermal management for PEM fuel cells.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Thermodynamics

Ultra-high fuel utilization in polymer electrolyte fuel cells part I: An experimental study

X. G. Yang, Y. Wang, C. Y. Wang

Summary: The study proposed and experimentally verified a high fuel utilization approach for polymer electrolyte fuel cells using ultra-low hydrogen stoichiometry supply. The approach was found to be feasible under different pressures and humidification conditions, providing stable cell performance. However, unstable operation regimes were observed under low power conditions, mainly influenced by air stoichiometry.

INTERNATIONAL JOURNAL OF GREEN ENERGY (2022)

Article Thermodynamics

Ultrahigh fuel utilization in polymer electrolyte fuel cells - Part II: A modeling study

Yun Wang, Xiaoguang Yang, Chao-Yang Wang

Summary: The numerical study showed that under ultrahigh fuel utilization, the anode flow slowed down significantly when using pure hydrogen fuel, but remained high in hydrogen concentration, alleviating concerns of fuel starvation and increased anode overpotential. Experimental instability in fuel cell operation at low current density may be due to water removal relying mostly on cathode channel flow.

INTERNATIONAL JOURNAL OF GREEN ENERGY (2022)

Article Energy & Fuels

Porous media flow field for polymer electrolyte membrane fuel cell: Depression of gas diffusion layer intrusion, deformation, and delamination

Bo Zheng, Zhe Wang, Yun Wang

Summary: This study investigates the application of porous media flow fields in polymer electrolyte membrane fuel cells and finds that porous media can effectively enhance thermal removal, electron conduction, and two-phase flow control, while reducing GDL intrusion and deformation and mitigating the risk of GDL/MPL delamination.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2022)

Article Chemistry, Physical

A modeling study of PEM fuel cells with novel catalyst monolayers under low platinum loading

Jingtian Wu, Huiyuan Liu, Yujiang Song, Yun Wang

Summary: This study investigates the reaction rate and distribution of oxygen and liquid water in polymer electrolyte membrane fuel cells with catalyst layers using three-dimensional modeling. The results show that the catalyst layers have a low effective exchange current density due to a low electrochemical surface area (ECSA) and operate with low oxygen content at low voltages. This leads to significant in-plane variation of the oxygen reduction reaction (ORR) rate, particularly with air cathode reactant flow. The through-plane ORR variations are smaller due to the thin catalyst layer thickness. To improve the performance of the low Pt loading novel catalyst layers, it is necessary to increase the ECSA and the gas diffusion layer (GDL) oxygen diffusivity considerably.

JOURNAL OF MATERIALS CHEMISTRY A (2022)

Article Electrochemistry

Spatial Variations of Cathode Reaction and Discharge Precipitate in Li-Air Batteries: Analysis and Experimental Measurement

Hao Yuan, Bongjin Seo, Yun Wang

Summary: In this study, the spatial variations of discharge precipitate and cathode reaction rate in lithium-air battery were investigated theoretically and experimentally. The results provide insights for designing and optimizing air cathode materials for Li-air batteries.

JOURNAL OF THE ELECTROCHEMICAL SOCIETY (2022)

Article Energy & Fuels

A component-level model of polymer electrolyte membrane electrolysis cells for hydrogen production

Daniela Fernanda Ruiz Diaz, Edgar Valenzuela, Yun Wang

Summary: This paper develops a component-level PEMEC model that incorporates various key factors of a PEMEC electrolysis cell. The model is validated and shown to accurately predict the performance of PEMEC. It can be used for the design and optimization of PEMEC components.

APPLIED ENERGY (2022)

Article Energy & Fuels

Convolutional neural network analysis of radiography images for rapid water quantification in PEM fuel cell

Yiheng Pang, Liang Hao, Yun Wang

Summary: This study presents a machine learning approach using convolutional neural networks to analyze neutron radiography images and quantify liquid water content in polymer electrolyte membrane fuel cells. The results show that using low relative humidity inlet flow can significantly reduce water content, while counter-flow configuration increases water content compared to co-flow configuration.

APPLIED ENERGY (2022)

Article Thermodynamics

Full-scale three-dimensional simulation of air-cooled proton exchange membrane fuel cell stack: Temperature spatial variation and comprehensive validation

Guobin Zhang, Zhiguo Qu, Yun Wang

Summary: This study conducted a full-scale stack three-dimensional simulation for proton exchange membrane (PEM) fuel cell and investigated the temperature distribution, cell/stack performance, and impact of air cooling. The research found that there are significant temperature differences between the fuel cells on the two sides and in the middle, and that higher temperature sites have lower oxygen content due to increased water vapor concentration. It was also found that increasing the cooling air flow rate decreases stack temperature and reduces temperature variation, thus benefiting the uniform distribution of gases in the stack.

ENERGY CONVERSION AND MANAGEMENT (2022)

Review Chemistry, Multidisciplinary

Towards ultralow platinum loading proton exchange membrane fuel cells

Linhao Fan, Hao Deng, Yingguang Zhang, Qing Du, Dennis Y. C. Leung, Yun Wang, Kui Jiao

Summary: With the global commercialization of PEMFCs approaching, the challenges of cost, performance, and durability need to be addressed. Developing ultralow Pt loading PEMFCs is crucial for improving their cost competitiveness. This perspective discusses the motivation for ultralow Pt loading and presents important technical development routes. The latest advancements in catalyst layer design under low Pt loading, as well as approaches for accelerating catalyst layer development, are proposed for next-generation PEMFCs.

ENERGY & ENVIRONMENTAL SCIENCE (2023)

Article Chemistry, Physical

Cross flow and distribution characteristics in automobile polymer electrolyte membrane fuel cells: A three-dimensional full-scale modeling study

Ning Wang, Zhiguo Qu, Guobin Zhang, Zetian Tang, Yun Wang

Summary: Ultrahigh power density is crucial for the commercialization of next-generation PEMFCs, particularly in large-size PEMFCs for automobile applications. This study uses a three-dimensional two-phase model to investigate the performance of an automobile fuel cell with various distribution zones. The results show that the dot matrix distribution zone can effectively promote cross flow between adjacent channels, mitigating oxygen starvation and water flooding and improving PEMFC performance at high current density. The counter-flow configuration also leads to higher cell performance and more uniform current density due to internal humidification.

JOURNAL OF POWER SOURCES (2023)

Article Materials Science, Multidisciplinary

Viscosity mechanism of perfluorosulfonic acid-based materials and their application in proton exchange membrane fuel cells

Cong Feng, Jin Zheng, Yun Wang, Cunman Zhang, Pingwen Ming

Summary: The viscosity characteristics and mechanical behavior of perfluorosulfonic acid (PFSA) ionomers were investigated in this study. A cross-scale model was developed to describe the shear thinning phenomenon, and a modified generalised Maxwell model was proposed to analyze the visco-elastoplastic behavior. The study provides insights into the mechanical response of PFSA ionomers under different strain rates.

APPLIED MATERIALS TODAY (2023)

Article Energy & Fuels

Proton exchange membrane fuel cell of integrated porous bipolar plate-gas diffusion layer structure: Entire morphology simulation

Guobin Zhang, Zhiguo Qu, Yun Wang

Summary: This study investigated an innovative proton exchange membrane (PEM) fuel cell design called the integrated porous bipolar plate (BP)-gas diffusion layer (GDL) structure. A three-dimensional (3D) fuel cell model was used to mimic the morphology of the integrated structure and validated using experimental polarization data. The novel design, which used metal foam as both the BP/flow field and GDL, significantly increased cell power density by reducing mass transfer and electron conduction resistances, and by decreasing overall cell thickness through GDL elimination. Smaller pore size (e.g., 60 to 80 PPI) was also found to improve power output and uniform distributions of oxygen and current density.

ETRANSPORTATION (2023)

Article Chemistry, Physical

Fluorine-decorated high loading Fe-N-C electrocatalysts for proton exchange membrane fuel cells

Rui Gao, Zhongyu Qiu, Kun Xu, Zihui Zhai, Yuanyuan Cong, Qike Jiang, Guanghui Zhang, Yang Lv, Yizheng Guo, Yongpeng Li, Qingchuan Xu, Yi Xiao, Yiheng Pang, Yun Wang, Yujiang Song

Summary: In this study, F-decorated Fe-N-C was synthesized by pyrolysis of trifluoromethyl imidazole decorated zeolitic imidazolate framework-8 with hemin as Fe precursor. F-Fe-N-C exhibits exceptional activity with high half-wave potential and single cell power density. The enhancement in performance is attributed to the high activity of F-Fe-N-C, abundant pore volume, and scattered distribution of ionomer.

JOURNAL OF MATERIALS CHEMISTRY A (2023)

Article Multidisciplinary Sciences

Enhancing oxygen transport in the ionomer film on platinum catalyst using ionic liquid additives

Linhao Fan, Yun Wang, Kui Jiao

Summary: This study found that adding an ionic liquid can effectively improve the structure of the ultrathin sublayer on the ionomer film, enhancing the O-2 transport efficiency and reducing the O-2 transport loss in the catalyst layer of the proton exchange membrane fuel cell.

FUNDAMENTAL RESEARCH (2022)

Review Chemistry, Multidisciplinary

PEM Fuel cell and electrolysis cell technologies and hydrogen infrastructure development - a review

Yun Wang, Yiheng Pang, Hui Xu, Andrew Martinez, Ken S. Chen

Summary: PEM fuel cells and PEM electrolysis cells are closely related electrochemical devices that operate at low temperatures and have the potential for wide applications. However, cost and the lack of hydrogen infrastructure are major challenges for their widespread deployment.

ENERGY & ENVIRONMENTAL SCIENCE (2022)

Article Energy & Fuels

Theoretical and experimental investigation on the advantages of auxetic nonlinear vortex-induced vibration energy harvesting

Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou

Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.

APPLIED ENERGY (2024)

Article Energy & Fuels

Evaluation method for the availability of solar energy resources in road areas before route corridor planning

Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan

Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.

APPLIED ENERGY (2024)

Article Energy & Fuels

Impacts of PTL coating gaps on cell performance for PEM water electrolyzer

Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender

Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.

APPLIED ENERGY (2024)

Article Energy & Fuels

Coordinated pricing mechanism for parking clusters considering interval-guided uncertainty-aware strategies

Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado

Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.

APPLIED ENERGY (2024)

Article Energy & Fuels

The establishment of evaluation systems and an index for energy superpower

Duan Kang

Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.

APPLIED ENERGY (2024)

Article Energy & Fuels

A model-based study of the evolution of gravel layer permeability under the synergistic blockage effect of sand particle transport and secondary hydrate formation

Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang

Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.

APPLIED ENERGY (2024)

Article Energy & Fuels

Energy optimization for HVAC systems in multi-VAV open offices: A deep reinforcement learning approach

Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi

Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Asymmetry stagger array structure ultra-wideband vibration harvester integrating magnetically coupled nonlinear effects

Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong

Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.

APPLIED ENERGY (2024)

Article Energy & Fuels

Enhancement of hydrogen production via optimizing micro-structures of electrolyzer on a microfluidic platform

Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song

Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel day-ahead scheduling model to unlock hydropower flexibility limited by vibration zones in hydropower-variable renewable energy hybrid system

Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz

Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.

APPLIED ENERGY (2024)

Article Energy & Fuels

Archery-inspired catapult mechanism with controllable energy release for efficient ultralow-frequency energy harvesting

Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He

Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy

Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang

Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Capacity fade prediction for vanadium redox flow batteries during long-term operations

Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung

Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.

APPLIED ENERGY (2024)

Article Energy & Fuels

State-of-charge balancing strategy of battery energy storage units with a voltage balance function for a Bipolar DC mircrogrid

Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu

Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.

APPLIED ENERGY (2024)

Article Energy & Fuels

Deep clustering of reinforcement learning based on the bang-bang principle to optimize the energy in multi-boiler for intelligent buildings

Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen

Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.

APPLIED ENERGY (2024)