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Cited by 247 publications
(113 citation statements)
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“…From a literature review, it is observed that most fuel cell PHM studies focus on the diagnostic stage, which can be loosely divided into two groups: model-based methods and data-driven techniques. Although several studies employ a model-based method for fuel cell diagnostics, i.e., developing a fuel cell model, and identifying fuel cell faults from residuals between model outputs and actual measurements [4][5][6][7][8], there are complexities in developing an accurate fuel cell model containing complete sets of failure modes. Data-driven approaches are more widely used for fuel cell diagnostics, that is, extracting the features by applying signal processing techniques to the sensor data, and discriminating fuel cell faults with extracted features [9][10][11][12][13].…”
Section: Introductionmentioning
confidence: 99%
“…From a literature review, it is observed that most fuel cell PHM studies focus on the diagnostic stage, which can be loosely divided into two groups: model-based methods and data-driven techniques. Although several studies employ a model-based method for fuel cell diagnostics, i.e., developing a fuel cell model, and identifying fuel cell faults from residuals between model outputs and actual measurements [4][5][6][7][8], there are complexities in developing an accurate fuel cell model containing complete sets of failure modes. Data-driven approaches are more widely used for fuel cell diagnostics, that is, extracting the features by applying signal processing techniques to the sensor data, and discriminating fuel cell faults with extracted features [9][10][11][12][13].…”
Section: Introductionmentioning
confidence: 99%
“…Despite the complexities, methods are developed to predict Fuel Cell State of Health (SoH) in terms of performance loss, degradation and, fault detection and isolation (FDI) [45,63,[74][75][76][77][78][79]. Diagnostic methods available are model or non-model based [71,[80][81][82][83][84]. Model-based methods are further classified as white, grey or black box depending on the nature of input and output.…”
Section: Pemfc Life Prediction Methods Under Aeronautic Conditionsmentioning
confidence: 99%
“…Model-based methods are further classified as white, grey or black box depending on the nature of input and output. The Black box model is most suitable for PEMFC since it is directly derived from experiments, requires little computational effort and, capable of on-line Figure 9: Electrochemical Impedance Spectrometry (1) and cyclic voltammograms (2) of fresh and MEA subjected to load cycling monitoring, detection and diagnostic applications [81]. In cases of very short transient periods, model-based methods such as statistics and knowledge of physical or electrical phenomena become useful.…”
Section: Pemfc Life Prediction Methods Under Aeronautic Conditionsmentioning
confidence: 99%
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“…However, these problems can be solved by means of the PEMFC technical state diagnostics [3][4][5][6] adopted to detect and possibly predict failures at the initial stages and to try to neutralize the e ects of failures to keep high operational characteristics. Development of corresponding methods and systems is an extremely di cult task since PEMFC operation is determined by several factors (pressure, reactant gases humidi cation, cell temperature, electrical operation mode, and others) and also considerably depends on the current technical state of membrane electrodes assembly and gas transport channels [1,[7][8][9].…”
Section: Introductionmentioning
confidence: 99%