Implementation of Integrated Thermal and Humidification Subsystems of 6 kW PEM Fuel Cell System

Improper humidification of reactant gasses and operating with non optimal temperature values are main factors influencing fast degradation of the most expensive element of PEM fuel cell stack, i.e. polymer electrolyte membrane. The thermal subsystem keeps fuel cell stack temperature at desired level to achieve optimal conditions of fuel cell operation . The humidification subsystem ensures the ionic conduction which is a basic element of working the PEM. Since water as a by-product of the fuel cell is an element used in both subsystems whereas heat supports a humidification process, both subsystem were integrated. The paper focuses on modeling and implementation of the both subsystems of 6 kW PEM fuel cell stack. In the first chapter of the paper, a mathematical model of the thermal subsystem is presented. Then, a selection of the thermal and humidification subsystems elements were considered. At the end of the paper, conclusions are included and further researches are shortly presented.

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Fault Diagnosis of Practical Polymer Electrolyte Membrane (PEM) Fuel Cell System with Data-driven Approaches

Fuel Cells ◽

10.1002/fuce.201600139 ◽

2016 ◽

Vol 17 (2) ◽

pp. 247-258 ◽

Cited By ~ 17

Author(s):

L. Mao ◽

L. Jackson ◽

S. Dunnett

Keyword(s):

Fuel Cell ◽

Fault Diagnosis ◽

Polymer Electrolyte ◽

Polymer Electrolyte Membrane ◽

Pem Fuel Cell ◽

Cell System ◽

Data Driven ◽

Fuel Cell System ◽

Electrolyte Membrane

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Research on the Fault Diagnosis of a Polymer Electrolyte Membrane Fuel Cell System

Energies ◽

10.3390/en13102531 ◽

2020 ◽

Vol 13 (10) ◽

pp. 2531

Author(s):

Feng Han ◽

Ying Tian ◽

Qiang Zou ◽

Xin Zhang

Keyword(s):

Fuel Cell ◽

Fault Diagnosis ◽

Polymer Electrolyte Membrane ◽

Pem Fuel Cell ◽

Cell System ◽

Support Vector ◽

Fuel Cell System ◽

Electrolyte Membrane ◽

Bee Colony ◽

Original Dataset

In this work, the possibilistic fuzzy C-means clustering artificial bee colony support vector machine (PFCM-ABC-SVM) method is proposed and applied for the fault diagnosis of a polymer electrolyte membrane (PEM) fuel cell system. The innovation of this method is that it can filter data with Gaussian noise and diagnose faults under dynamic conditions, and the amplitude of characteristic parameters is reduced to ±10%. Under dynamic conditions with Gaussian noise, the faults of the PEM fuel cell system are simulated and the original dataset is established. The possibilistic fuzzy C-means (PFCM) algorithm is used to filter samples with membership and typicality less than 90% and to optimize the original dataset. The artificial bee colony (ABC) algorithm is used to optimize the penalty factor C and kernel function parameter g. Finally, the optimized support vector machine (SVM) model is used to diagnose the faults of the PEM fuel cell system. To illustrate the results of the fault diagnosis, a nonlinear PEM fuel cell simulator model which has been presented in the literature is used. In addition, the PFCM-ABC-SVM method is compared with other methods. The result shows that the method can diagnose faults in a PEM fuel cell system effectively and the accuracy of the testing set sample is up to 98.51%. When solving small-sized, nonlinear, high-dimensional problems, the PFCM-ABC-SVM method can improve the accuracy of fault diagnosis.

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Potential Usage of Thermoelectric Devices in a High-Temperature Polymer Electrolyte Membrane (PEM) Fuel Cell System: Two Case Studies

Journal of Electronic Materials ◽

10.1007/s11664-012-2098-2 ◽

2012 ◽

Vol 41 (6) ◽

pp. 1838-1844 ◽

Cited By ~ 16

Author(s):

Xin Gao ◽

Min Chen ◽

Søren Juhl Andreasen ◽

Søren Knudsen Kær

Keyword(s):

High Temperature ◽

Fuel Cell ◽

Polymer Electrolyte ◽

Case Studies ◽

Polymer Electrolyte Membrane ◽

Pem Fuel Cell ◽

Cell System ◽

Fuel Cell System ◽

Thermoelectric Devices ◽

Electrolyte Membrane

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Overcoming the Challenges for a Mass Manufacturing Machine for the Assembly of PEMFC Stacks

Machines ◽

10.3390/machines7040066 ◽

2019 ◽

Vol 7 (4) ◽

pp. 66 ◽

Cited By ~ 3

Author(s):

Porstmann ◽

Wannemacher ◽

Richter

Keyword(s):

Fuel Cell ◽

Economies Of Scale ◽

Polymer Electrolyte Membrane ◽

Cell System ◽

Active Components ◽

Fuel Cell Stack ◽

Electrolyte Membrane ◽

Modular Concept ◽

A Cell ◽

Manufacturing Machine

One of the major obstacles standing in the way of a break-through in fuel cell technology is its relatively high costs compared to well established fossil-based technologies. The reasons for these high costs predominantly lie in the use of non-standardized components, complex system components, and non-automated production of fuel cells. This problem can be identified at multiple levels, for example, the electrochemically active components of the fuel cell stack, peripheral components of the fuel cell system, and eventually on the level of stack and system assembly. This article focused on the industrialization of polymer electrolyte membrane fuel cell (PEMFC) stack components and assembly. To achieve this, the first step is the formulation of the requirement specifications for the automated PEMFC stack production. The developed mass manufacturing machine (MMM) enables a reduction of the assembly time of a cell fuel cell stack to 15 minutes. Furthermore the targeted automation level is theoretically capable of producing up to 10,000 fuel cell stacks per year. This will result in a ~50% stack cost reduction through economies of scale and increased automation. The modular concept is scalable to meet increasing future demand which is essential for the market ramp-up and success of this technology.

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