연구동향 분석

Fault response and severity-based fault diagnostic method for polymer electrolyte membrane fuel cell system = 고분자 전해질막 연료전지 시스템 고장 반응 및 심각도 기반 고장진단 방법

박진영 2021년

논문상세정보
인용/피인용
' Fault response and severity-based fault diagnostic method for polymer electrolyte membrane fuel cell system = 고분자 전해질막 연료전지 시스템 고장 반응 및 심각도 기반 고장진단 방법' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 응용 물리
  • Degradation
  • Fault diagnosis
  • Fault severity
  • Local current distribution
  • Neural network
  • Polymer electrolyte membrane fuel cell system
  • 고분자 전해질막 연료전지 시스템
  • 고장 심각도
  • 고장 진단
  • 국소 전류밀도 분포
  • 뉴럴 네트워크
  • 열화
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
1,255 0

0.0%

' Fault response and severity-based fault diagnostic method for polymer electrolyte membrane fuel cell system = 고분자 전해질막 연료전지 시스템 고장 반응 및 심각도 기반 고장진단 방법' 의 참고문헌

  • “ Two-phase cooling using HFE- 7100 for polymer electrolyte membrane fuel cell application , ”
    E. J. ChoiJ. Y . ParkM. S. Kim Appl . Therm . Eng.vol . 148 , no . August 2018pp . 868 ? 877 [2019]
  • “ The effect of relative humidity of the cathode on the performance and the uniformity of PEM fuel cells , ”
    D. H. JeonK. N. KimS. M. BaekJ. H. Nam Int . J. Hydrogen Energyvol . 36 , no . 19 , pp . 12499 ? 12511 [2011]
  • “ The effect of low humidity on the uniformity and stability of segmented PEM fuel cells , ”
    F.-B . WengB.-S. JouC.-W. LiA. SuS.-H. Chan J . Power Sourcesvol . 181 , no . 2 , pp . 251 ? 258 [2008]
  • “ Technology Acceleration : Fuel Cell Bus Evaluations , ”
    L. Eudy Online ] . Available : https : //www.osti.gov/servlets/purl/1518591 [2019]
  • “ SunLine Transit Agency American Fuel Cell Bus Progress Report , Data Period Focus : January 2017 ? July 2019 , ”
    L. Eudy and M. PostOnline ] . Available : https : //www.osti.gov/servlets/purl/1659871 [2020]
  • “ Study on the Uncoupling Characteristics of PEM Fuel Cell by Segmented Cell Technology , ”
    B. FengR. LinD. LiuD. Zhong Int . J. Electrochem . Scivol . 14 , pp . 2175 ? 2186 [2019]
  • “ Study on the Current Density Distribution in Polymer Electrolyte Membrane Fuel Cell
    Y.H . Lee PEMFC ) System '' , Seoul National University [2020]
  • “ Study on a purge method using pressure reduction for effective water removal in polymer electrolyte membrane fuel cells , ”
    Y. S. KimS. Il KimN. W. LeeM. S. Kim Int . J. Hydrogen Energyvol . 40 , no . 30 , pp . 9473 ? 9484 [2015]
  • “ Study of internal multi-parameter distributions of proton exchange membrane fuel cell with segmented cell device and coupled three-dimensional model , ”
    C. YinY. GaoT. LiG. XieK. LiH. Tang Renew . Energyvol . 147 , pp . 650 ? 662 [2020]
  • “ Spatially resolved degradation during startup and shutdown in polymer electrolyte membrane fuel cell operation , ”
    S. Komini Babu et al. Appl . Energyvol . 254 , no . October 2018 , p. 113659 [2019]
  • “ Simultaneous visualization of oxygen partial pressure , current density , and water droplets in serpentine fuel cell during power generation for understanding reaction distributions , ”
    K. Takanohashi et al. J . Power Sourcesvol . 343 , pp . 135 ? 141 [2017]
  • “ Segmented cell approach for studying uniformity of current distribution in polymer electrolyte fuel cell operation , ”
    S.-G. KimM.-J . KimY.-J . Sohn Int . J. Hydrogen Energyvol . 40 , no . 35 , pp . 11676 ? 11685 [2015]
  • “ Residual-based fault diagnosis for thermal management systems of proton exchange membrane fuel cells , ”
    H. OhW. Y. LeeJ . WonM. KimY. Y. ChoiS. Bin Han Appl . Energyvol . 277 , p. 115568 [2020]
  • “ Research trends in proton exchange membrane fuel cells during 2008 ? 2018 : A bibliometric analysis , ”
  • “ Real-time analysis of dry start-up characteristics of polymer electrolyte membrane fuel cell with water storage process under pressurized condition , ”
    Y. S. KimD. K. KimK. Y. AhnM. S. Kim Energy , p. 117292 [2020]
  • “ Prediction of local current distribution in polymer electrolyte membrane fuel cell with artificial neural network , ”
    J. Y . ParkY. H. LeeI. S. LimY. S. KimM. S. Kim Int . J. Hydrogen Energyvol . 46 , no . 39 , 2021 , pp.20678-20692 , 2021
  • “ Performance prediction of a proton exchange membrane fuel cell using the ANFIS model
    Y. VuralD. B. InghamM. Pourkashanian Int . J. Hydrogen Energyvol . 34 , no . 22 , pp . 9181 ? 9187 [2009]
  • “ Performance prediction of PEM fuel cell with wavy serpentine flow channel by using artificial neural network , ”
    M. SeyhanY. E. AkansuM. MuratY. KorkmazS. O. Akansu Int . J. Hydrogen Energyvol . 42 , no . 40 , pp . 25619 ? 25629 [2017]
  • “ Performance prediction and analysis of a PEM fuel cell operating on pure oxygen using data-driven models : A comparison of artificial neural network and support vector machine , ”
    I.-S. HanC.-B . Chung Int . J. Hydrogen Energyvol . 41 , no . 24 , pp . 10202 ? 10211 [2016]
  • “ Parametric study on the local current distribution of polymer electrolyte membrane fuel cell with counter flow channel under pressurized condition , ”
    Y. S. KimD. K. KimK. Y. AhnM. S. Kim J. Mech . Sci . Technol.vol . 34 , no . 5 , pp . 2189 ? 2198 [2020]
  • “ Parametric analysis of simultaneous humidification and cooling for PEMFCs using direct water injection method , ”
    E. J. ChoiS. H. HwangJ . ParkM. S. Kim Int . J. Hydrogen Energyvol . 42 , no . 17 , pp . 12531 ? 12542 [2017]
  • “ PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques , ”
    A. EscobetF. Mugica Appl . Artif . Intelligencevol . 36 , pp . 40 ? 53 [2014]
  • “ Optimizing the relative humidity to improve the stability of a proton exchange membrane by segmented fuel cell technology , ”
    R. LinC. CaoJ. MaE. G ? lzowK. A. Friedrich Int . J. Hydrogen Energyvol . 37 , no . 4 , pp . 3373 ? 3381 [2012]
  • “ Operating strategy for successful start-up in self-humidified polymer electrolyte membrane fuel-cell system , ”
    Y. S. KimD. K. Kim Appl . Therm . Eng.vol . 152 , pp . 370 ? 376 [2019]
  • “ Online implementation of SVM based fault diagnosis strategy for PEMFC systems , ”
    Z. Li et al. Appl . Energyvol . 164 , pp . 284-293 [2016]
  • “ On the distribution of local current density along a PEM fuel cell cathode channel , ”
    T. ReshetenkoA. Kulikovsky Electrochem . commun.vol . 101 , pp . 35 ? 38 [2019]
  • “ Neural network modeling of proton exchange membrane fuel cell , ”
    S. V PuranikA. KeyhaniF. Khorrami IEEE Trans . Energy Convers.vol . 25 , no . 2 , pp . 474 ? 483 [2010]
  • “ Neural network model for a commercial PEM fuel cell system , ”
    A. SaengrungA. AbtahiA. Zilouchian J . Power Sourcesvol . 172 , no . 2 , pp . 749 ? 759 [2007]
  • “ Model based PEM fuel cell state-of-health monitoring via ac impedance measurements , ”
    N. FouquetC. DouletC. NouillantG. Dauphin-TanguyB. Ould-Bouamama J . Power Sourcesvol . 159 , no . 2 , pp . 905 ? 913 [2006]
  • “ Materials , technological status , and fundamentals of PEM fuel cells ? A review
    Y. WangD. F. Ruiz DiazK. S. ChenZ. WangX. C. Adroher Mater . Todayvol . 32 , pp . 178 ? 203 [2020]
  • “ Local resolved investigation of PEMFC performance degradation mechanism during dynamic driving cycle , ”
    J. ShanR. LinS. XiaD. LiuQ. Zhang Int . J. Hydrogen Energyvol . 41 , no . 7 , pp . 4239 ? 4250 [2016]
  • “ Local electrochemical characteristics at various operating pressure and temperature values using a segmented polymer electrolyte membrane fuel cell , ”
    Y. S. KimD. K. KimI. M. KongM. KimM. S. Kim J. Mech . Sci . Technol.vol . 30 , no . 9 , pp . 4391 ? 4396 [2016]
  • “ LPV observer design for PEM fuel cell system : Application to fault detection , ”
    S. De LiraV. PuigJ. QuevedoA. Husar J . Power Sourcesvol . 196 , no . 9 , pp . 4298 ? 4305 [2011]
  • “ Investigation of the nonuniform distribution of current density in commercial-size proton exchange membrane fuel cells , ”
    L. PengH. ShaoD. QiuP. YiX. Lai J . Power Sourcesvol . 453 , p. 227836 [2020]
  • “ Investigation of real-time changes and recovery of proton exchange membrane fuel cell in voltage reversal , ”
    R. Lin et al. Energy Convers . Manag.vol . 236 , p. 114037 , 2021
  • “ Investigation of dynamic driving cycle effect on the degradation of proton exchange membrane fuel cell by segmented cell technology , ”
    R. LinF. XiongW. C. TangL. T ? cherJ. M. ZhangJ. X. Ma J . Power Sourcesvol . 260 , pp . 150 ? 158 [2014]
  • “ Influence of the microporous layer on carbon corrosion in the catalyst layer of a polymer electrolyte membrane fuel cell , ”
    D. SpernjakJ. FairweatherR. MukundanT. RockwardR. L. Borup J . Power Sourcesvol . 214 , pp . 386 ? 398 [2012]
  • “ In-situ measurement of temperature and humidity distribution in gas channels for commercialsize proton exchange membrane fuel cells , ”
    H. ShaoD. QiuL. PengP. YiX. Lai J . Power Sourcesvol . 412 , pp . 717 ? 724 [2019]
  • “ In-situ diagnostics and degradation mapping of a mixed-mode accelerated stress test for proton exchange membranes , ”
    Y. H. LaiG. W. Fly J . Power Sourcesvol . 274 , pp . 1162 ? 1172 [2015]
  • “ In situ investigation of proton exchange membrane fuel cell performance with novel segmented cell design and a two-phase flow model , ”
    C. Yin et al. Energyvol . 113 , pp . 1071 ? 1089 [2016]
  • “ In situ approach for current distribution measurement in fuel cells , ”
    P. C. GhoshT. WH. DohleN. KimiaieJ. MergelD. Stolten J . Power Sourcesvol . 154 , no . 1 , pp . 184 ? 191 [2006]
  • “ Implementation of sensor based on neural networks technique to predict the PEM fuel cell hydration state , ”
    F. Z. AramaK. MammarS. LaribiA. NecaibiaT. Ghaitaoui J . Energy Storagevol . 27 , p. 101051 [2020]
  • “ Impedance model for diagnosis of water management in fuel cells using artificial neural networks methodology , ”
    S. LaribiK. MammarM. HamoudaY. Sahli Int . J. Hydrogen Energyvol . 41 , no . 38 , pp . 17093 ? 17101 [2016]
  • “ Impact of flow rates and electrode specifications on degradations during repeated startups and shutdowns in polymerelectrolyte membrane fuel cells , ”
    J. Dillet et al. J . Power Sourcesvol . 250 , pp . 68 ? 79 [2014]
  • “ Hierarchical fault diagnostic method for a polymer electrolyte fuel cell system , ”
    W. Y. LeeH. OhM. KimY. Y. ChoiY. J. SohnS. G. Kim Int . J. Hydrogen Energyvol . 45 , no . 47 , pp.25733- 25746 [2020]
  • “ Fuel Cell Electric Vehicle Durability and Fuel Cell Performance , ”
    J. KurtzS. SprikG. SaurS. Onorato Online ] . Available : www.nrel.gov/publications [2018]
  • “ Fault tree analysis for PEM fuel cell degradation process modelling
    L. PlaccaR. Kouta Int . J. Hydrogen Energyvol . 36 , no . 19 , pp . 12393 ? 12405 [2011]
  • “ Fault diagnosis of thermal management system in a polymer electrolyte membrane fuel cell , ”
    J. Y . ParkI. S. LimE. J. ChoiM. S. Kim Energyvol . 214 , p. 119062 , 2021
  • “ Fault detection and isolation for PEM fuel cell stack with independent RBF model , ”
    M. M. KamalD. W. YuD. L. Yu Appl . Artif . Intell.vol . 28 , pp . 52 ? 63 [2014]
  • “ Experimental investigation of PEM fuel cell aging under current cycling using segmented fuel cell , ”
    F. B. WengC. Y. HsuC. W. Li Int . J. Hydrogen Energyvol . 35 , no . 8 , pp . 3664 ? 3675 [2010]
  • “ Empirical modeling of polymer electrolyte membrane fuel cell performance using artificial neural networks , ”
    W. Y. LeeG. G. ParkT. H. YangY. G. YoonC. S. Kim Int . J. Hydrogen Energyvol . 29 , no . 9 , pp . 961 ? 966 [2004]
  • “ Electrochemical impedance spectroscopy of catalyst and carbon degradations in proton exchange membrane fuel cells , ”
    Q. MeyerY. ZengC. Zhao J . Power Sourcesvol . 437 , no . May , p. 226922 [2019]
  • “ Electrochemical impedance analysis with transmission line model for accelerated carbon corrosion in polymer electrolyte membrane fuel cells , ”
    J. Jung et al. Int . J. Hydrogen Energyvol . 43 , no . 32 , pp . 15457 ? 15465 [2018]
  • “ Efficient fault diagnosis method of PEMFC thermal management system for various current densities , ”
    I. S. LimJ. Y . ParkE. J. ChoiM. S. Kim Int . J. Hydrogen Energyvol . 46 , no . 2 , pp . 2543 ? 2554 , 2021
  • “ Effect of operating conditions on the performance of a PEM fuel cell , ”
    H. Askaripour Int . J . Heat Mass Transf.vol . 144 , p. 118705 [2019]
  • “ Effect of operating conditions on current density distribution and high frequency resistance in a segmented PEM fuel cell , ”
    D. GerteisenN. ZamelC. SadelerF. GeigerV. LudwigC. Hebling Int . J. Hydrogen Energyvol . 37 , no . 9 , pp . 7736 ? 7744 [2012]
  • “ Diagnosis of polymer electrolyte fuel cells failure modes ( flooding & drying out ) by neural networks modeling , ”
    N. Yousfi SteinerD. HisselP. Mot ? guyD. Candusso Int . J. Hydrogen Energyvol . 36 , no . 4 , pp . 3067 ? 3075 [2011]
  • “ Development of a lightweight fuel cell vehicle , ”
    J. J. HwangD. Y. WangN. C. Shih J . Power Sourcesvol . 141 , no . 1 , pp . 108 ? 115 [2005]
  • “ Degradation Mechanisms in Automotive Fuel Cell Systems. ”
    G. RadicaF. B. Fesb FCH-JU , GIANTLEAP [2017]
  • “ Data-driven diagnosis of PEM fuel cell : A comparative study , ”
    Z. LiR. OutbibD. HisselS. Giurgea Control Eng . Pract.vol . 28 , pp . 1 ? 12 [2014]
  • “ Data driven models for a PEM fuel cell stack performance prediction , ”
    G. NapoliM. FerraroF. SergiG. BrunacciniV. Antonucci Int . J. Hydrogen Energyvol . 38 , no . 26 , pp . 11628 ? 11638 [2013]
  • “ Current distribution mapping for PEMFCs , ” Electrochim
    V. LilavivatS. ShimpaleeJ. W. Van ZeeH. XuC. K. Mittelsteadt Acta , vol . 174 , pp . 1253 ? 1260 [2015]
  • “ Current distribution in a single cell of PEMFC
    Y.-G. YoonW.-Y . LeeT.-H. YangG.-G. ParkC.-S. Kim J . Power Sourcesvol . 118 , no . 1 ? 2 , pp . 193 ? 199 [2003]
  • “ Current density distribution in PEFC , ”
    Z. LiuZ. MaoB. WuL. WangV. M. Schmidt J . Power Sourcesvol . 141 , no . 2 , pp . 205 ? 210 [2005]
  • “ Computational Justification of Current Distribution Measurement Technique Via Segmenting Bipolar Plate in Fuel Cells , ”
    Y.-J . ChoiG.-Y . LeeK.-M. KangW.-G. KimH.-C. Ju Transactions of the Korean hydrogen and new energy society , vol . 21 , no . 1. pp . 1 ? 11 [2010]
  • “ Comparative study of reverse flow activation and conventional activation with polymer electrolyte membrane fuel cell , ”
    J. Y . ParkI. S. LimE. J. ChoiY. H. LeeM. S. Kim Renew . Energyvol . 167 , pp . 162 ? 171 , 2021
  • “ Characterization of Carbon Corrosion in a Segmented PEM Fuel Cell , ”
    D. SpernjakJ. D. FairweatherT. RockwardR. MukundanR. Borup ECS Trans.vol . 41 , no . 1 , pp . 741 ? 750 [2019]
  • “ Carbon Corrosion in PEM Fuel Cells and the Development of Accelerated Stress Tests , ”
    N. Macauley et al. J. Electrochem . Soc.vol . 165 , no . 6 , pp . F3148 ? F3160 [2018]
  • “ Behaviors of proton exchange membrane fuel cells under oxidant starvation , ”
    M. Dou et al. J . Power Sourcesvol . 196 , no . 5 , pp . 2759 ? 2762 [2011]
  • “ Behavior of a unit proton exchange membrane fuel cell in a stack under fuel starvation
    D. LiangM. DouM. HouQ. ShenZ. ShaoB. Yi J . Power Sourcesvol . 196 , no . 13 , pp . 5595 ? 5598 [2011]
  • “ Artificial Neural Network Modeling of PEM Fuel Cells , ”
    S. OuL. E. K. Achenie J . Fuel Cell SciTechnol. , vol . 2 , no . 4 , pp . 226 ? 233 [2005]
  • “ Analyzing in-plane temperature distribution via a micro-temperature sensor in a unit polymer electrolyte membrane fuel cell , ”
    H. Y. WangW. J. YangY . B. Kim Appl . Energyvol . 124 , pp . 148 ? 155 [2014]
  • “ Analytical solutions and dimensional analysis of pseudo 2D current density distribution model in PEM fuel cells , ”
    S. ChevalierC. JossetB. Auvity Renew . energyvol . 125 , pp . 738 ? 746 [2018]
  • “ Analysis and diagnosis of PEM fuel cell failure modes ( flooding & drying ) across the physical parameters of electrochemical impedance model : Using neural networks method , ”
    S. LaribiK. MammarY. SahliK. Koussa Sustain . Energy Technol . Assessmentsvol . 34 , pp . 35 ? 42 [2019]
  • “ An artificial neural network ensemble method for fault diagnosis ofproton exchange membrane fuel cell system , ”
    M. ShaoX. J. ZhuH. F. CaoH. F. Shen Energyvol . 67 , pp . 268 ? 275 [2014]
  • “ An analysis of fluidic voltage statistical correlation for a diagnosis of PEM fuel cell flooding , ”
    S. GiurgeaR. TirnovanD. HisselR. Outbib Int . J. Hydrogen Energyvol . 38 , no . 11 , pp . 4689 ? 4696 [2013]
  • “ A survey of fault diagnosis and fault-tolerant techniques-part I : Fault diagnosis with model-based and signal-based approaches , ”
    Z. GaoC. CecatiS. X. Ding IEEE Trans . Ind . Electron.vol . 62 , no . 6 , pp . 3757 ? 3767 [2015]
  • “ A signal-based method for fast PEMFC diagnosis , ”
    E. PahonN. Yousfi SteinerS. JemeiD. HisselP. Mo ? oteguy Appl . Energyvol . 165 , pp . 748 ? 758 [2016]
  • “ A segmented cell approach for studying the effects of serpentine flow field parameters on PEMFC current distribution , ”
    T. V ReshetenkoG. BenderK. BethuneR. Rocheleau Electrochim . Actavol . 88 , pp . 571 ? 579 [2013]
  • “ A review on prognostics and health monitoring of proton exchange membrane fuel cell , ”
    T. SutharssanD. MontalvaoY. K. ChenW. C. WangC. PisacH. Elemara Renew . Sustain . Energy Reviewsvol . 75 , pp . 440 ? 450 [2017]
  • “ A review on non-model based diagnosis methodologies for PEM fuel cell stacks and systems , ”
    Z. Zheng et al. Int . J. Hydrogen Energyvol . 38 , no . 21 , pp . 8914 ? 8926 [2013]
  • “ A review on model-based diagnosis methodologies for PEMFCs , ”
    R. Petrone et al. Int . J. Hydrogen Energyvol . 38 , no . 17 , pp . 7077 ? 7091 [2013]
  • “ A novel technique for measuring current distributions in PEM fuel cells , ”
    H. SunG. ZhangL.-J . GuoH. Liu J . Power Sourcesvol . 158 , no . 1 , pp . 326 ? 332 [2006]
  • “ A novel diagnostic methodology for fuel cell stack health : performance , consistency and uniformity
    Z. Hu et al. Energy Convers . Manag.vol . 185 , pp . 611 ? 621 [2019]
  • “ A new modeling approach of embedded fuel-cell power generators based on artificial neural network , ”
    S. JemeD. HisselJ. M. Kauffmann IEEE Trans . Ind . Electron.P ? raPeravol . 55 , no . 1 , pp . 437 ? 447 [2008]
  • “ A double-fuzzy diagnostic methodology dedicated to online fault diagnosis of proton exchange membrane fuel cell stacks , ”
    Z. ZhengM. C. PD. HisselM. BecherifK. S. AgbliY. Li J . Power Sourcesvol . 271 , pp . 570 ? 581 [2014]
  • “ A comparison of temperature distribution in PEMFC with single-phase water cooling and two-phase HFE-7100 cooling methods by numerical study , ”
    E. J. ChoiJ. Y . ParkM. S. Kim Int . J. Hydrogen Energy [2018]
  • “ A Printed Circuit Board approach to measuring current distribution in a fuel cell , ”
    S. J. C. CleghornC. R. DerouinM. S. WilsonS. Gottesfeld J. Appl . Electrochem.vol . 28 , no . 7 , pp . 663 ? 672 [1998]
  • ot ? guy“ A review on polymer electrolyte membrane fuel cell catalyst degradation and starvation issues : Causes , consequences and diagnostic for mitigation
    N. Yousfi-SteinerP. MoD. CandussoD. Hissel J . Power Sourcesvol . 194 , no . 1 , pp . 130 ? 145 [2009]
  • `` H2 @ Scale Workshop Report , ''
    B. Pivovar Online ] . Available : https : //www.osti.gov/servlets/purl/1350015 [2017]
  • `` Fault Detection and Diagnosis Methods for Polymer Electrolyte Fuel Cell System , ”
    W. Y. LeeY. J. SohnS. G. KimM. Kim Trans . of Korean Hydrogen and New Energy Society , vol . 28 , no . 3 , pp . 252 ? 272 [2017]
  • E. Baltacıo ? lu , and K. Aydın , “ Overview of the next quarter century vision of hydrogen fuel cell electric vehicles , ”
    B . TanH. T. Arat Int . J. Hydrogen Energyvol . 44 , no . 20 , pp . 10120 ? 10128 [2019]
  • Atlas of Electrochemical Equilibria in Aqueous Solutions
    M. Pourbaix New York : Pergamon Press [1966]
  • A. U. Ch ? vez-Ram ? rez et al. , “ High power fuel cell simulator based on artificial neural network
    Int . J. Hydrogen Energyvol . 35 , no . 21 , pp . 12125 ? 12133 [2010]
  • , “ Investigating the effect of start-up and shut-down cycles on the performance of the proton exchange membrane fuel cell by segmented cell technology ,
    ] R., X., J., L. T ?, F.and Q. ” Int . J. Hydrogen, vol . 40 , no . 43 , pp . 14952 ? [,]