A Reduced Fuel Cell Stack Model for Control and Fault Diagnosis

2006 ◽  
Vol 3 (4) ◽  
pp. 384-388 ◽  
Author(s):  
Damiano Di Penta ◽  
Karim Bencherif ◽  
Michel Sorine ◽  
Qinghua Zhang
Keyword(s):  
Fuel Cell ◽  
Fault Diagnosis ◽  
Gas Adsorption ◽  
Carbon Monoxide Poisoning ◽  
Important Indicator ◽  
Fuel Cell Stack ◽  
Electrode Potentials ◽  
The Difference ◽  
Adsorption Desorption ◽  
Stack Model

This paper proposes a reduced fuel cell stack model for control and fault diagnosis which was validated with experimental data. Firstly, the electro-chemical phenomena are modeled based on a mechanism of gas adsorption/desorption on catalysts at the anode and at the cathode of the stack, including activation, diffusion, and carbon monoxide poisoning. The electrical voltage of a stack cell is then modeled by the difference between the two electrode potentials. A simplified thermal model of the fuel cell stack is also developed in order to take into account heat generation from reactions, heat transfers, and evaporation/condensation of water. Finally, the efficiency ratio is computed as a model output. It is used to evaluate the efficiency changes of the entire system, providing an important indicator for fault detection.

scholarly journals Brain-inspired computational paradigm dedicated to fault diagnosis of PEM fuel cell stack

2017 ◽  
Vol 42 (8) ◽  
pp. 5410-5425 ◽  
Author(s):  
Zhixue Zheng ◽  
Simon Morando ◽  
Marie-Cécile Pera ◽  
Daniel Hissel ◽  
Laurent Larger ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Fault Diagnosis ◽  
Pem Fuel Cell ◽  
Fuel Cell Stack ◽  
Computational Paradigm

Performance Analysis of Solid Oxide Fuel Cell Stack: Part 1 — Model Description and Validation

2007 ◽  
Author(s):  
Vittorio Verda ◽  
Michele Cali`
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Solid Oxide ◽  
Model Description ◽  
Current Transfer ◽  
Oxide Fuel ◽  
Cfd Model ◽  
Detailed Model ◽  
Fuel Cell Stack ◽  
Stack Model

In this paper a detailed model for the simulation of a tubular solid oxide fuel cell stack is presented. The model solves heat transfer, current transfer and fluid flow in the stack. The effect of mass transfer is accounted by means of the information provided by a CFD model of a single cell. The approach used to build the model allows one to simulate large stacks, predicting the temperature, current and mass flow rate profiles. The model has been applied to the CHP100 manufactured by Siemens. The results obtained by the stack model are compared with some of the available measurements.

A spatially resolved fuel cell stack model with gas–liquid slip phenomena for cold start simulations

2017 ◽  
Vol 42 (22) ◽  
pp. 15328-15346 ◽  
Author(s):  
Tian Tang ◽  
Steffen Heinke ◽  
André Thüring ◽  
Wilhelm Tegethoff ◽  
Jürgen Köhler
Keyword(s):  
Fuel Cell ◽  
Cold Start ◽  
Fuel Cell Stack ◽  
Spatially Resolved ◽  
Stack Model

Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2366
Author(s):  
Guangying Jin ◽  
Guangzhe Jin
Keyword(s):  
Decision Making ◽  
Fuel Cell ◽  
Fault Diagnosis ◽  
Optimal Solution ◽  
Sensor Selection ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Fuel Cell Stack ◽  
Asymmetric Problem ◽  
Selection Methodology

Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. However, in light of the choosing of fault diagnosis sensors, there is no MCDM analysis, and Fuel Cell Stack companies also urgently need a solution. Therefore, in this paper, we will use MCDM methods to analysis the fault-diagnosis sensor selection problem for the first time. The main contribution of this paper is to proposed a fault-diagnosis sensor selection methodology, which combines the rank reversal resisted AHP and TOPSIS and supports Fuel Cell Stack companies to select the optimal fault-diagnosis sensors. Apart from that, through the analysis, among all sensor alternatives, the acquisition of the optimal solution can be regarded as solving the symmetric or asymmetric problem of the optimal solution, which just maps to the TOPSIS method. Therefore, after apply the proposed fault-diagnosis sensor selection methodology, the Fuel Cell Stack system fault-diagnosis process will be more efficient, economical, and safe.

Sign in / Sign up

Export Citation Format

Share Document