IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v303y2021ics0306261921010072.html
   My bibliography  Save this article

Quantitative analysis of internal polarization dynamics for polymer electrolyte membrane fuel cell by distribution of relaxation times of impedance

Author

Listed:
  • Yuan, Hao
  • Dai, Haifeng
  • Ming, Pingwen
  • Wang, Xueyuan
  • Wei, Xuezhe

Abstract

Investigating and interpreting each internal polarization dynamics that occurs in the polymer electrolyte membrane fuel cell is significant. Traditional equivalent circuit model fitting by nonlinear least-squares relies on prior model assumptions and initial value selection of components. In this paper, the distribution of relaxation times methodology with powerful separating ability is applied to reveal a more precise analysis of polarization processes. First, the electrochemical impedance spectroscopy under a broad of operating conditions is carried out. Four polarization dynamics related to oxygen transfer, charge transfer of the oxygen reduction, proton transfer inside cathode ionomer, and interface contact process between catalyst layer and membrane (perhaps, including anode oxidation reaction) are effectively extracted. Then, a fourth-order equivalent circuit model established via distribution of relaxation times results is introduced to quantify the loss of each polarization process. Based on this, for the first time, the sensitivity of each polarization loss against operating conditions is analyzed by the multiple stepwise regression analysis, and its application on vehicular fuel cell system control is discussed. Afterward, the distribution of relaxation times is also first to explore the loss and variation trend of each polarization process under flooding, membrane drying, and air starvation fault, where each failure type contains at least eight test sequences. These efforts represent a comprehensive and systematic guideline for fuel cells using distribution of relaxation times, which can also guide the study of degradation mechanisms, optimization design of materials, and even other electrochemical energy sources.

Suggested Citation

  • Yuan, Hao & Dai, Haifeng & Ming, Pingwen & Wang, Xueyuan & Wei, Xuezhe, 2021. "Quantitative analysis of internal polarization dynamics for polymer electrolyte membrane fuel cell by distribution of relaxation times of impedance," Applied Energy, Elsevier, vol. 303(C).
  • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921010072
    DOI: 10.1016/j.apenergy.2021.117640
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921010072
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.117640?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhong, Di & Lin, Rui & Jiang, Zhenghua & Zhu, Yike & Liu, Dengchen & Cai, Xin & Chen, Liang, 2020. "Low temperature durability and consistency analysis of proton exchange membrane fuel cell stack based on comprehensive characterizations," Applied Energy, Elsevier, vol. 264(C).
    2. Salva, J. Antonio & Iranzo, Alfredo & Rosa, Felipe & Tapia, Elvira, 2016. "Validation of cell voltage and water content in a PEM (polymer electrolyte membrane) fuel cell model using neutron imaging for different operating conditions," Energy, Elsevier, vol. 101(C), pages 100-112.
    3. Zhang, Xiaojie & Zhang, Tong & Chen, Huicui & Cao, Yinliang, 2021. "A review of online electrochemical diagnostic methods of on-board proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 286(C).
    4. Yuan, Hao & Dai, Haifeng & Wei, Xuezhe & Ming, Pingwen, 2020. "A novel model-based internal state observer of a fuel cell system for electric vehicles using improved Kalman filter approach," Applied Energy, Elsevier, vol. 268(C).
    5. Kim, Bosung & Cha, Dowon & Kim, Yongchan, 2015. "The effects of air stoichiometry and air excess ratio on the transient response of a PEMFC under load change conditions," Applied Energy, Elsevier, vol. 138(C), pages 143-149.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiaping Xie & Chao Wang & Wei Zhu & Hao Yuan, 2021. "A Multi-Stage Fault Diagnosis Method for Proton Exchange Membrane Fuel Cell Based on Support Vector Machine with Binary Tree," Energies, MDPI, vol. 14(20), pages 1-22, October.
    2. Zhao, Lei & Yuan, Hao & Xie, Jiaping & Jiang, Shangfeng & Wei, Xuezhe & Tang, Wei & Ming, Pingwen & Dai, Haifeng, 2023. "Inconsistency evaluation of vehicle-oriented fuel cell stacks based on electrochemical impedance under dynamic operating conditions," Energy, Elsevier, vol. 265(C).
    3. Zhao, Lei & Hong, Jichao & Xie, Jiaping & Jiang, Shangfeng & Wei, Xuezhe & Ming, Pingwen & Dai, Haifeng, 2023. "Investigation of local sensitivity for vehicle-oriented fuel cell stacks based on electrochemical impedance spectroscopy," Energy, Elsevier, vol. 262(PA).
    4. Yuan, Hao & Zhou, Shulin & Zhang, Shaozhe & Tang, Wei & Jiang, Bo & Wei, Xuezhe & Dai, Haifeng, 2024. "Unconventional frequency response analysis of PEM fuel cell based on high-order frequency response function and total harmonic distortion," Applied Energy, Elsevier, vol. 357(C).
    5. Li, Haolong & Wei, Wei & Liu, Fengxia & Xu, Xiaofei & Li, Zhiyi & Liu, Zhijun, 2023. "Identification of internal polarization dynamics for solid oxide fuel cells investigated by electrochemical impedance spectroscopy and distribution of relaxation times," Energy, Elsevier, vol. 267(C).
    6. Yuan, Hao & Dai, Haifeng & Ming, Pingwen & Li, Sida & Wei, Xuezhe, 2022. "A new insight into the effects of agglomerate parameters on internal dynamics of proton exchange membrane fuel cell by an advanced impedance dimension model," Energy, Elsevier, vol. 253(C).
    7. Zhao, Jian & Li, Xianguo & Shum, Chris & McPhee, John, 2023. "Control-oriented computational fuel cell dynamics modeling – Model order reduction vs. computational speed," Energy, Elsevier, vol. 266(C).
    8. Li, Sida & Wei, Xuezhe & Jiang, Shangfeng & Yuan, Hao & Ming, Pingwen & Wang, Xueyuan & Dai, Haifeng, 2022. "Hydrogen crossover diagnosis for fuel cell stack: An electrochemical impedance spectroscopy based method," Applied Energy, Elsevier, vol. 325(C).
    9. Jiaping Xie & Hao Yuan & Yufeng Wu & Chao Wang & Xuezhe Wei & Haifeng Dai, 2023. "Impedance Acquisition of Proton Exchange Membrane Fuel Cell Using Deeper Learning Network," Energies, MDPI, vol. 16(14), pages 1-18, July.
    10. Zhang, Xuexia & Huang, Lei & Jiang, Yu & Lin, Long & Liao, Hongbo & Liu, Wentao, 2024. "Investigation of nonlinear accelerated degradation mechanism in fuel cell stack under dynamic driving cycles from polarization processes," Applied Energy, Elsevier, vol. 355(C).
    11. Wei, Manhui & Wang, Keliang & Pei, Pucheng & Zuo, Yayu & Zhong, Liping & Shang, Nuo & Wang, Hengwei & Chen, Junfeng & Zhang, Pengfei & Chen, Zhuo, 2022. "An enhanced-performance Al-air battery optimizing the alkaline electrolyte with a strong Lewis acid ZnCl2," Applied Energy, Elsevier, vol. 324(C).
    12. Xinjie Xu & Kai Li & Zhenjie Liao & Jishen Cao & Renkang Wang, 2022. "A Closed-Loop Water Management Methodology for PEM Fuel Cell System Based on Impedance Information Feedback," Energies, MDPI, vol. 15(20), pages 1-16, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pei, Pucheng & Meng, Yining & Chen, Dongfang & Ren, Peng & Wang, Mingkai & Wang, Xizhong, 2023. "Lifetime prediction method of proton exchange membrane fuel cells based on current degradation law," Energy, Elsevier, vol. 265(C).
    2. Dong Zhu & Yanbo Yang & Tiancai Ma, 2022. "Evaluation the Resistance Growth of Aged Vehicular Proton Exchange Membrane Fuel Cell Stack by Distribution of Relaxation Times," Sustainability, MDPI, vol. 14(9), pages 1-19, May.
    3. Abdin, Z. & Webb, C.J. & Gray, E.MacA., 2016. "PEM fuel cell model and simulation in Matlab–Simulink based on physical parameters," Energy, Elsevier, vol. 116(P1), pages 1131-1144.
    4. Lin, Rui & Zhong, Di & Lan, Shunbo & Guo, Rong & Ma, Yunyang & Cai, Xin, 2021. "Experimental validation for enhancement of PEMFC cold start performance: Based on the optimization of micro porous layer," Applied Energy, Elsevier, vol. 300(C).
    5. Ren, Peng & Pei, Pucheng & Li, Yuehua & Wu, Ziyao & Chen, Dongfang & Huang, Shangwei & Jia, Xiaoning, 2019. "Diagnosis of water failures in proton exchange membrane fuel cell with zero-phase ohmic resistance and fixed-low-frequency impedance," Applied Energy, Elsevier, vol. 239(C), pages 785-792.
    6. Wu, Kangcheng & Du, Qing & Zu, Bingfeng & Wang, Yupeng & Cai, Jun & Gu, Xin & Xuan, Jin & Jiao, Kui, 2021. "Enabling real-time optimization of dynamic processes of proton exchange membrane fuel cell: Data-driven approach with semi-recurrent sliding window method," Applied Energy, Elsevier, vol. 303(C).
    7. Xu, Liangfei & Fang, Chuan & Hu, Junming & Cheng, Siliang & Li, Jianqiu & Ouyang, Minggao & Lehnert, Werner, 2017. "Parameter extraction of polymer electrolyte membrane fuel cell based on quasi-dynamic model and periphery signals," Energy, Elsevier, vol. 122(C), pages 675-690.
    8. Wang, Qianqian & Tang, Fumin & Li, Bing & Dai, Haifeng & Zheng, Jim P. & Zhang, Cunman & Ming, Pingwen, 2022. "Investigation of the thermal responses under gas channel and land inside proton exchange membrane fuel cell with assembly pressure," Applied Energy, Elsevier, vol. 308(C).
    9. Pan, Mingzhang & Pan, Chengjie & Li, Chao & Zhao, Jian, 2021. "A review of membranes in proton exchange membrane fuel cells: Transport phenomena, performance and durability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    10. Moazeni, Faegheh & Khazaei, Javad, 2020. "Electrochemical optimization and small-signal analysis of grid-connected polymer electrolyte membrane (PEM) fuel cells for renewable energy integration," Renewable Energy, Elsevier, vol. 155(C), pages 848-861.
    11. Zhang, Zhuo & Wang, Qi-yao & Bai, Fan & Chen, Li & Tao, Wen-quan, 2023. "Performance simulation and key parameters in-plane distribution analysis of a commercial-size PEMFC," Energy, Elsevier, vol. 263(PC).
    12. Liu, Ze & Zhang, Baitao & Xu, Sichuan, 2022. "Research on air mass flow-pressure combined control and dynamic performance of fuel cell system for vehicles application," Applied Energy, Elsevier, vol. 309(C).
    13. Meng, Huanru & Yu, Xianxian & Luo, Xiaobing & Tu, Zhengkai, 2024. "Modelling and operation characteristics of air-cooled PEMFC with metallic bipolar plate used in unmanned aerial vehicle," Energy, Elsevier, vol. 300(C).
    14. Zhu, Yunlong & Dong, Zhe & Cheng, Zhonghua & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2023. "Neural network extended state-observer for energy system monitoring," Energy, Elsevier, vol. 263(PA).
    15. Kwang-Hu Jung & Jung-Hyung Lee, 2024. "Determination of an Optimal Parameter Combination for Single PEMFC Using the Taguchi Method and Orthogonal Array," Energies, MDPI, vol. 17(7), pages 1-11, April.
    16. Ren, Peng & Meng, Yining & Pei, Pucheng & Fu, Xi & Chen, Dongfang & Li, Yuehua & Zhu, Zijing & Zhang, Lu & Wang, Mingkai, 2023. "Rapid synchronous state-of-health diagnosis of membrane electrode assemblies in fuel cell stacks," Applied Energy, Elsevier, vol. 330(PA).
    17. Baricci, Andrea & Mereu, Riccardo & Messaggi, Mirko & Zago, Matteo & Inzoli, Fabio & Casalegno, Andrea, 2017. "Application of computational fluid dynamics to the analysis of geometrical features in PEM fuel cells flow fields with the aid of impedance spectroscopy," Applied Energy, Elsevier, vol. 205(C), pages 670-682.
    18. Zeng, Tao & Zhang, Caizhi & Hao, Dong & Cao, Dongpu & Chen, Jiawei & Chen, Jinrui & Li, Jin, 2020. "Data-driven approach for short-term power demand prediction of fuel cell hybrid vehicles," Energy, Elsevier, vol. 208(C).
    19. Fan, Lixin & Tu, Zhengkai & Chan, Siew Hwa, 2022. "Technological and Engineering design of a megawatt proton exchange membrane fuel cell system," Energy, Elsevier, vol. 257(C).
    20. Jiaping Xie & Chao Wang & Wei Zhu & Hao Yuan, 2021. "A Multi-Stage Fault Diagnosis Method for Proton Exchange Membrane Fuel Cell Based on Support Vector Machine with Binary Tree," Energies, MDPI, vol. 14(20), pages 1-22, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921010072. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.