PEM Fuel Cell System Modeling with Liquid Fuel Processing and Hydrogen Membranes

2019 ◽  
Vol 3 (1) ◽  
pp. 1139-1148
Author(s):  
Gregory S. Jackson ◽  
Eric Shields ◽  
Joshua Pearlman ◽  
Seyed Abdolreza Seyed-Reihani ◽  
Atul Bhargav ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Liquid Fuel ◽  
System Modeling ◽  
Pem Fuel Cell ◽  
Cell System ◽  
Fuel Cell System ◽  
Fuel Processing

Dynamic Simulation of a Stationary PEM Fuel Cell System

2006 ◽  
Author(s):  
Kyoungdoug Min ◽  
Jack Brouwer ◽  
John Auckland ◽  
Fabian Mueller ◽  
Scott Samuelsen
Keyword(s):  
Fuel Cell ◽  
System Performance ◽  
Processing System ◽  
Temperature Shift ◽  
Pem Fuel Cell ◽  
Cell System ◽  
System Model ◽  
Fuel Cell System ◽  
Fuel Processing ◽  
Control Volumes

A dynamic model of a stationary PEM fuel cell system has been developed in Matlab-Simulink®. The system model accounts for the fuel processing system, PEM stack with coolant, humidifier with anode tail-gas oxidizer (ATO), and an enthalpy wheel for cathode air. For the fuel processing system four reactors were modeled: (1) an auto thermal reactor (ATR) (2) a high temperature shift (HTS) reactor, (3) a low temperature shift (LTS) reactor, and (4) a preferential oxidation (PROX) reactor. Chemical kinetics for ATR that describe steam reformation of methane and partial oxidation of methane were simultaneously solved to accurately predict the reaction dynamics. Chemical equilibrium of CO with H2O was assumed at HTS and LTS reactor exits to calculate CO conversion corresponding to the temperature of each reactor. A quasi-two dimensional unit PEM cell was modeled with five control volumes for solving the dynamic species and mass conservation equations and seven control volumes to solve the dynamic energy balance and to capture the details of MEA behavior, such as water transport, which is critical to accurately determine polarization losses. The dynamic conservation equations, primary heat transfer equations and equations of state are solved in each bulk component and each component is linked together to represent the complete system. A comparison of steady-state model results to experimental data shows that the system model well predicts the actual system power and catalytic partial oxidation (CPO) temperature. Transient simulation of DC power is also well matched with the experimental results to within a few percent. The model predictions well characterized the observed dynamic CPO temperature, voltage, and temperature of stack coolant outlet observations that are representative of a generic PEM stationary fuel cell system performance. The model is shown to be a useful tool for investigating the effects of inlet conditions and for the development of control strategies for enhancing system performance.

scholarly journals Balanced version of Slime Mold Algorithm: A study on PEM fuel cell system parameters identification

2021 ◽  
Vol 7 ◽  
pp. 3199-3209
Author(s):  
Junlong Zheng ◽  
Yujie Xie ◽  
Xiaoping Huang ◽  
Zhongxing Wei ◽  
Bahman Taheri
Keyword(s):  
Fuel Cell ◽  
Pem Fuel Cell ◽  
Cell System ◽  
Slime Mold ◽  
Parameters Identification ◽  
Fuel Cell System ◽  
System Parameters

Development of a Portable LPG PEM Fuel Cell System

2019 ◽  
Vol 12 (1) ◽  
pp. 671-680
Author(s):  
Ju-Yong Kim ◽  
SungChul Lee ◽  
WooCheol Shin ◽  
YongGul Lee ◽  
DongHyun Kim
Keyword(s):  
Fuel Cell ◽  
Pem Fuel Cell ◽  
Cell System ◽  
Fuel Cell System

scholarly journals Performance Improvement by Temperature Control of an Open-Cathode PEM Fuel Cell System

Fuel Cells ◽  
2014 ◽  
Vol 14 (3) ◽  
pp. 466-478 ◽  
Author(s):  
S. Strahl ◽  
A. Husar ◽  
P. Puleston ◽  
J. Riera
Keyword(s):  
Fuel Cell ◽  
Performance Improvement ◽  
Temperature Control ◽  
Pem Fuel Cell ◽  
Cell System ◽  
Fuel Cell System
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