Efficient fault diagnosis of proton exchange membrane fuel cell using external magnetic field measurement

被引:15
|
作者
Liu, Zhongyong [1 ]
Sun, Yuning [1 ]
Mao, Lei [1 ,2 ]
Zhang, Heng [3 ]
Jackson, Lisa [4 ]
Wu, Qiang [1 ]
Lu, Shouxiang [5 ]
机构
[1] Univ Sci & Technol China, Dept Precis Machinery & Precis Instrumentat, Hefei, Peoples R China
[2] Univ Sci & Technol China, Inst Adv Technol, Hefei, Peoples R China
[3] Hefei Univ, Sch Artificial Intelligence & Big Data, Hefei, Peoples R China
[4] Loughborough Univ, Dept Aeronaut & Automot Engn, Loughborough, England
[5] Univ Sci & Technol China, State Key Lab Fire Sci, Hefei, Peoples R China
基金
中国国家自然科学基金;
关键词
Proton exchange membrane fuel cell; Fault diagnosis; Model simulation; Water management; Magnetic field; COMPONENT ANALYSIS; WATER MANAGEMENT; PEMFC; ELECTROLYTE; MODEL; METHODOLOGIES; TEMPERATURE; RESISTANCE; STACKS; TOOL;
D O I
10.1016/j.enconman.2022.115809
中图分类号
O414.1 [热力学];
学科分类号
摘要
Fault diagnosis has been considered as a critical solution for improving the reliability of proton exchange membrane fuel cell (PEMFC) system. This study proposes an efficient PEMFC fault diagnosis technique, where PEMFC external magnetic field is measured during its operation, from which PEMFC performance degradation mechanisms and corresponding faults can be identified. In the analysis, a PEMFC numerical model is constructed to explore the relation between external magnetic field and PEMFC state of health. Furthermore, a non-invasive measurement strategy is proposed to collect external magnetic field during the operation. With the measurements, an efficient PEMFC fault diagnosis method is proposed, and its effectiveness in identifying PEMFC water management issues is investigated using PEMFC test data. Results demonstrate that PEMFC flooding and dehydration can be discriminated with good quality, and the faulty level can also be identified accurately.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Fault Diagnosis of Proton Exchange Membrane Fuel Cell Using Magnetic Field Data
    Sun, Yuning
    Mao, Lei
    Huang, Weiguo
    Zhang, Heng
    Lu, Shouxiang
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2022, 58 (22): : 106 - 114
  • [2] The Fault Analysis and Diagnosis of Proton Exchange Membrane Fuel Cell Stack
    Lin, Zhen
    Wang, Changhui
    Liu, Yu
    NEW AND ADVANCED MATERIALS, PTS 1 AND 2, 2011, 197-198 : 705 - 710
  • [3] A Review on Fault Diagnosis tools of the Proton Exchange Membrane Fuel Cell
    Salim, Reem I.
    Noura, Hassan
    Fardoun, Abbas
    2013 2ND INTERNATIONAL CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), 2013, : 686 - 693
  • [4] Fault diagnosis methods for Proton Exchange Membrane Fuel Cell system
    Benmouna, A.
    Becherif, M.
    Depernet, D.
    Gustin, F.
    Ramadan, H. S.
    Fukuhara, S.
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (02) : 1534 - 1543
  • [5] Fault Diagnosis of Proton Exchange Membrane Fuel Cells
    Allam, A.
    Mangold, M.
    Zhang, P.
    5TH CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL 2021), 2021, : 366 - 371
  • [6] Review and Prospect of Fault Diagnosis Methods for Proton Exchange Membrane Fuel Cell
    Chen W.
    Liu J.
    Li Q.
    Guo A.
    Dai C.
    2017, Chinese Society for Electrical Engineering (37): : 4712 - 4721
  • [7] A Review on Water Fault Diagnosis of a Proton Exchange Membrane Fuel Cell System
    Ma, Tiancai
    Zhang, Zhaoli
    Lin, Weikang
    Yang, Yanbo
    Yao, Naiyuan
    JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE, 2021, 18 (03)
  • [8] Fault Diagnosis of Proton Exchange Membrane Fuel Cell Based on Nonlinear Impedance Spectrum
    Yuan, Hao
    Zhang, Shaozhe
    Wei, Xuezhe
    Dai, Haifeng
    AUTOMOTIVE INNOVATION, 2023, 6 (04) : 597 - 610
  • [9] Fault diagnosis of proton exchange membrane fuel cell based on nonlinear dynamic model
    Yong J.
    Zhao Q.
    Feng N.
    Huagong Xuebao/CIESC Journal, 2022, 73 (09): : 3983 - 3993
  • [10] Fault Diagnosis of Proton Exchange Membrane Fuel Cell Based on Nonlinear Impedance Spectrum
    Hao Yuan
    Shaozhe Zhang
    Xuezhe Wei
    Haifeng Dai
    Automotive Innovation, 2023, 6 : 597 - 610