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Fault diagnosis of thermal management system in a polymer electrolyte membrane fuel cell

https://doi.org/10.1016/j.energy.2020.119062
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2015.11.060openalex-snapshot
Online implementation of SVM based fault diagnosis strategy for PEMFC systems
inferredcites →https://doi.org/10.1016/j.applthermaleng.2018.11.103openalex-snapshot
Two-phase cooling using HFE-7100 for polymer electrolyte membrane fuel cell application
inferredcites →https://doi.org/10.1016/j.conengprac.2014.02.019openalex-snapshot
Data-driven diagnosis of PEM fuel cell: A comparative study
inferredcites →https://doi.org/10.1016/j.enconman.2018.12.049openalex-snapshot
The reactant starvation of the proton exchange membrane fuel cells for vehicular applications: A review
inferredcites →https://doi.org/10.1016/j.enconman.2019.02.031openalex-snapshot
A novel diagnostic methodology for fuel cell stack health: Performance, consistency and uniformity
inferredcites →https://doi.org/10.1016/j.energy.2014.01.079openalex-snapshot
An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system
inferredcites →https://doi.org/10.1016/j.engappai.2013.10.002openalex-snapshot
Fault detection and isolation for PEM fuel cell stack with independent RBF model
inferredcites →https://doi.org/10.1016/j.engappai.2014.07.008openalex-snapshot
PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques
inferredcites →https://doi.org/10.1016/j.ijhydene.2010.05.124openalex-snapshot
Neural network model of 100 W portable PEM fuel cell and experimental verification
inferredcites →https://doi.org/10.1016/j.ijhydene.2010.10.077openalex-snapshot
Diagnosis of polymer electrolyte fuel cells failure modes (flooding & drying out) by neural networks modeling
inferredcites →https://doi.org/10.1016/j.ijhydene.2011.06.093openalex-snapshot
Fault tree analysis for PEM fuel cell degradation process modelling
inferredcites →https://doi.org/10.1016/j.ijhydene.2011.07.094openalex-snapshot
The optimal design for PEMFC modeling based on Taguchi method and genetic algorithm neural networks
inferredcites →https://doi.org/10.1016/j.ijhydene.2013.03.106openalex-snapshot
A review on model-based diagnosis methodologies for PEMFCs
inferredcites →https://doi.org/10.1016/j.ijhydene.2013.04.007openalex-snapshot
A review on non-model based diagnosis methodologies for PEM fuel cell stacks and systems
inferredcites →https://doi.org/10.1016/j.ijhydene.2016.07.181openalex-snapshot
Fault diagnosis methods for Proton Exchange Membrane Fuel Cell system
inferredcites →https://doi.org/10.1016/j.ijhydene.2017.03.201openalex-snapshot
Parametric analysis of simultaneous humidification and cooling for PEMFCs using direct water injection method
inferredcites →https://doi.org/10.1016/j.ijhydene.2017.05.157openalex-snapshot
Techno-economic study of hydrogen production using CSP technology
inferredcites →https://doi.org/10.1016/j.ijhydene.2018.05.056openalex-snapshot
A comparison of temperature distribution in PEMFC with single-phase water cooling and two-phase HFE-7100 cooling methods by numerical study
inferredcites →https://doi.org/10.1016/j.jpowsour.2007.05.039openalex-snapshot
Neural network model for a commercial PEM fuel cell system
inferredcites →https://doi.org/10.1016/j.jpowsour.2008.12.014openalex-snapshot
Model-based fault diagnosis in PEM fuel cell systems
inferredcites →https://doi.org/10.1016/j.jpowsour.2010.11.084openalex-snapshot
LPV observer design for PEM fuel cell system: Application to fault detection
inferredcites →https://doi.org/10.1016/j.jpowsour.2014.07.157openalex-snapshot
A double-fuzzy diagnostic methodology dedicated to online fault diagnosis of proton exchange membrane fuel cell stacks
inferredcites →https://doi.org/10.1016/s0378-7753(03)00799-7openalex-snapshot
On-board fuel cell power supply modeling on the basis of neural network methodology
inferredcites →https://doi.org/10.1023/a:1007379606734openalex-snapshot
Multitask Learning
inferredcites →https://doi.org/10.1109/tie.2007.896480openalex-snapshot
A New Modeling Approach of Embedded Fuel-Cell Power Generators Based on Artificial Neural Network
inferredcites →https://doi.org/10.7316/khnes.2017.28.3.252openalex-snapshot
Fault Detection and Diagnosis Methods for Polymer Electrolyte Fuel Cell System

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4609481openalex-extracted
Reduced-Order Grey-Box Modeling of Flow-Through H2/O2 Polymer Electrolyte Membrane Fuel Cell Stack with Integrated Planar Membrane Humidifiers
inferred← citeshttps://doi.org/10.2139/ssrn.4637713openalex-extracted
Parameter Identification of H2/O2 Pem Fuel Stack with Integrated Planar Membrane Humidifiers
inferred← citeshttps://doi.org/10.2139/ssrn.4665212openalex-extracted
Parameter Identification of H2/O2 Polymer Electrolyte Membrane Fuel Stack with Integrated Planar Membrane Humidifiers
inferred← citeshttps://doi.org/10.1002/ente.202300132openalex-snapshot
Fault Diagnosis and Fault‐Tolerant Control Method for a Multistack Fuel Cell Thermal Management Subsystem
inferred← citeshttps://doi.org/10.1007/978-981-92-2897-3_25openalex-snapshot
Optimized Operation of Fuel Cell Systems Based on a Two-Layer Control Structure
inferred← citeshttps://doi.org/10.1016/b978-0-323-99485-9.00005-8openalex-snapshot
Lattice Boltzmann modeling and artificial intelligence
inferred← citeshttps://doi.org/10.1016/j.apenergy.2021.117735openalex-snapshot
Intelligent health states recognition of fuel cell by cell voltage consistency under typical operating parameters
inferred← citeshttps://doi.org/10.1016/j.apenergy.2022.120486openalex-snapshot
Severity-based fault diagnostic method for polymer electrolyte membrane fuel cell systems
inferred← citeshttps://doi.org/10.1016/j.apenergy.2025.126142openalex-snapshot
A review on thermal management strategy for liquid-cooling proton exchange membrane fuel cells: Temperature regulation and cold start
inferred← citeshttps://doi.org/10.1016/j.egyr.2022.05.036openalex-snapshot
Fuel cell diagnosis methods for embedded automotive applications
inferred← citeshttps://doi.org/10.1016/j.electacta.2021.139811openalex-snapshot
Probing the influence of nonuniform Pt particle size distribution using a full three-dimensional, multiscale, multiphase polymer electrolyte membrane fuel cell model
inferred← citeshttps://doi.org/10.1016/j.enconman.2022.115221openalex-snapshot
Thermal management of polymer electrolyte membrane fuel cells: A critical review of heat transfer mechanisms, cooling approaches, and advanced cooling techniques analysis
inferred← citeshttps://doi.org/10.1016/j.energy.2021.119909openalex-snapshot
Optimizing the structural design of cathode catalyst layer for PEM fuel cells for improving mass-specific power density
inferred← citeshttps://doi.org/10.1016/j.energy.2021.119951openalex-snapshot
The effect of cathode channel blockages on the enhanced mass transfer and performance of PEMFC
inferred← citeshttps://doi.org/10.1016/j.energy.2021.122298openalex-snapshot
A fault diagnosis method for small pressurized water reactors based on long short-term memory networks
inferred← citeshttps://doi.org/10.1016/j.energy.2022.124663openalex-snapshot
Neural network-based adaptive fault-tolerant control for load following of a MHTGR with prescribed performance and CRDM faults
inferred← citeshttps://doi.org/10.1016/j.fuel.2026.140678openalex-snapshot
Multi-scale optimization of metal foam flow fields for enhancing the fluid flow and heat transfer processes in air-cooled PEMFCs
inferred← citeshttps://doi.org/10.1016/j.ijhydene.2023.01.257openalex-snapshot
Towards Deep Computer Vision for In-Line Defect Detection in Polymer Electrolyte Membrane Fuel Cell Materials
inferred← citeshttps://doi.org/10.1016/j.ijhydene.2024.05.156openalex-snapshot
Critical quantitative evaluation of integrated health management methods for fuel cell applications
inferred← citeshttps://doi.org/10.1016/j.ijhydene.2024.07.190openalex-snapshot
Fault diagnosis of PEMFC based on fatal and recoverable failures using multi-scale convolutional neural networks
inferred← citeshttps://doi.org/10.1016/j.ijhydene.2024.09.227openalex-snapshot
Machine learning-based fault diagnosis for various steady conditions of proton exchange membrane fuel cell systems
inferred← citeshttps://doi.org/10.1016/j.ins.2025.122524openalex-snapshot
Fault diagnosis of proton exchange membrane fuel cell using multiple convolutional neural networks with multi-scale attention mechanism
inferred← citeshttps://doi.org/10.1016/j.renene.2021.07.079openalex-snapshot
Hybrid diagnosis method for initial faults of air supply systems in proton exchange membrane fuel cells
inferred← citeshttps://doi.org/10.1109/icetci68937.2026.11610687openalex-snapshot
Construction of a Feature Extraction Framework for Fault Diagnosis of Fuel Cell Vehicle Powertrain Systems
inferred← citeshttps://doi.org/10.1109/iecon48115.2021.9589511openalex-snapshot
A Novel Diagnosis Method of Proton Exchange Membrane Fuel Cells Based on Multi-Grained Cascade Forest and Principal Component Analysis
inferred← citeshttps://doi.org/10.1149/1945-7111/ae2a74openalex-snapshot
Experimental Study on Thermal Response Characteristics of Open-Cathode Proton Exchange Membrane Fuel Cell
inferred← citeshttps://doi.org/10.14447/jnmes.v26i1.a05openalex-snapshot
Accurate Estimation of PEMFC State of Health using Modified Hybrid Artificial Neural Network Models
inferred← citeshttps://doi.org/10.3390/en16083379openalex-snapshot
Development of Model-Based PEM Water Electrolysis HILS (Hardware-in-the-Loop Simulation) System for State Evaluation and Fault Detection
inferred← citeshttps://doi.org/10.3390/math10224306openalex-snapshot
Associated Fault Diagnosis of Power Supply Systems Based on Graph Matching: A Knowledge and Data Fusion Approach
inferred← citeshttps://doi.org/10.3390/pr12061140openalex-snapshot
Towards Reliable Prediction of Performance for Polymer Electrolyte Membrane Fuel Cells via Machine Learning-Integrated Hybrid Numerical Simulations
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