FDI oriented modeling of an experimental SOFC system, model validation and simulation of faulty states

Sorce, Alessandro; Greco, A.; Magistri, Loredana; Costamagna, Paola

doi:10.1016/j.apenergy.2014.03.074

Cited by 51 publications

(38 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The anode and the cathode channel dimensions of our cell are 0.45 mm × 0.45 mm. The value of Nusselt number from SOFC literature is ≈4.2 . Considering the fuel cell channel flow to be a fully developed laminar flow in a rectangular pipe, we have the following relation:

italicNu = \frac{{italichD}_{h}}{k_{f}}

…”

Section: Preliminary Model Validationmentioning

confidence: 99%

“…Because of the high number of uncertain parameters, model calibration is often performed for achieving compliance of the model predictions with the test results . However, no systematic method is followed in these works for the selection of the calibration parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Because of the high number of uncertain parameters, model calibration is often performed for achieving compliance of the model predictions with the test results. [15][16][17][18][19][20][21][22][23][24][25] However, no systematic method is followed in these works for the selection of the calibration parameters. A rational method for selecting appropriate parameters for calibration is the parameter sensitivity analysis.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Statistical method‐based calibration and validation of a solid oxide fuel cell model

2018

View full text Add to dashboard Cite

Summary A 2‐stage model validation strategy for the previously developed solid oxide fuel cell model using the data from custom‐designed experiments is presented. The strategy is based on the identification of model structural and parametric errors. In the preliminary validation, the causes that can result in the voltage error during changing temperature and fuel flow rate conditions are analysed. It is identified that the convection heat transfer process contributes significantly towards the cell performance in a temperature controlled test environment. Rectification of this error results in the reduction of the maximum voltage error from 14% to 0.5%. Graphical methods for data visualisation are utilised to examine goodness of fit of the model. Input sensitivity analysis reveals that the air flow rate has negligible influence on the output quantities of current density, fuel utilisation, and cell temperature owing to temperature‐controlled conditions of the test. Parameter sensitivity analysis through the elementary effects method reveals that most of the electrochemical parameters in general and the activation energies in particular have dominant effects on the considered system outputs. Model validation is carried out through a classical statistical method of hypothesis testing by using the parameter uncertainty information obtained through nonlinear least squares fitting. The efficacy of the model validation strategy is demonstrated through the model acceptance with 8% maximum error in cell current.

show abstract

italicNu = \frac{{italichD}_{h}}{k_{f}}

…”

Section: Preliminary Model Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Statistical method‐based calibration and validation of a solid oxide fuel cell model

2018

View full text Add to dashboard Cite

show abstract

“…Significant challenges arise in making SOFC systems responsive. Advanced integrated system controls, as explored in [15][16][17][18][19][20][21][22][23], are necessary in order to maintain system integrity, durability, and lifespan. Controller design is highly dependent upon the application requirements and system configuration, but generally thermal response should be damped to the extent possible, given the materials used and the high temperatures involved.…”

Section: Introductionmentioning

confidence: 99%

Investigation of thermal control for different SOFC flow geometries

2016

View full text Add to dashboard Cite

h i g h l i g h t s Thermal control of cross flow SOFC is investigated. Changing flow directions in a subset of channels can improve thermal profiles. Non uniform air flow improves thermal profile at the expense of small efficiency loss. Advanced controllers minimize thermal variations for large changes in power demand. a b s t r a c t A dynamic solid oxide fuel cell (SOFC) model is used to investigate the effects of different flow arrangements, as well as those of non-uniform air flow across channels, on temperature profile and thermal gradients under transient and steady state response. A high performance multi-input multi-output feedback controller has been developed to minimize SOFC spatial temperature variations during changes in power demands for different flow patterns. Numerical results show that the controller would result in negligible temperature variations for the modified cross-flow arrangement proposed here, even for large changes in the power drawn. The combination of a high performance controller and design modification results in a more uniform temperature profile at steady state nominal conditions, and modest variations in temperature profile, from the nominal, for ±15% change in power. Similarly, non-uniform air flow rate decreases the temperature gradient as well as maximum temperature across the cell, though its effect is less pronounced in the closed loop response.

show abstract

“…The importance of early detection, isolation, identification and possibly correction of faults, has been evidenced by previous research works on solid oxide fuel cell (SOFC) plants . With reference to the SOFC power plant scheme reported in (Figure , the possible types of faults have been grouped into four main categories (classes) , : (i) air leakage: this fault consists in leakage of air between the air blower and the SOFC stack itself; (ii) fuel leakage: in the reformer, the methane/steam feed is converted into a hydrogen rich mixture. Leakage is likely to occur between the exit of the reformer and the entrance of the SOFC stack because of the small dimensions and high diffusivity of the hydrogen molecule; (iii) SOFC stack degradation: an increase of the SOFC internal losses (activation, ohmic and diffusion losses) leads to a reduced electrochemical performance and efficiency.…”

Section: Introductionmentioning

confidence: 99%

Diagnostics and Prognostics‐Oriented Modeling of an NGSR Fuel Processor for Application in SOFC Systems

et al. 2017

Self Cite

View full text Add to dashboard Cite

Diagnostics and prognostics of natural gas steam reforming (NGSR) reactors are of utmost importance for solid oxide fuel cell (SOFC) systems, where a fuel processor fault can cause damage to the SOFC stack. Most common faults are due to carbon deposition. We investigate this phenomenon through a model based on microscopic mass, energy and momentum balances of a tubular NGSR reactor. The model includes a detailed local reaction kinetics specific for Ni-based catalysts, and is integrated numerically using a finite element method (FEM) implemented through COMSOL Multiphysics 5.2. Results obtained from the simulation of a laboratory scale reactor are validated on the basis of literature data. Furthermore, the model is applied to an NGSR fuel processor designed for an 1.1 kW SOFC system. The model allows to identify the area where carbon deposition is expected to occur, which is a key feature in view of developing specific diagnostic and prognostic tools. The simulation results demonstrate that safety criteria based on the feedstock steam to carbon (S/C) ratio can be misleading in a number of operating conditions.

show abstract

FDI oriented modeling of an experimental SOFC system, model validation and simulation of faulty states

Cited by 51 publications

References 54 publications

Statistical method‐based calibration and validation of a solid oxide fuel cell model

Statistical method‐based calibration and validation of a solid oxide fuel cell model

Investigation of thermal control for different SOFC flow geometries

Diagnostics and Prognostics‐Oriented Modeling of an NGSR Fuel Processor for Application in SOFC Systems

Contact Info

Product

Resources

About