Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Special Issues
Modelling and Process Control of Fuel Cell Systems
share announcement

Modelling and Process Control of Fuel Cell Systems

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 32392

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Mohd Azlan Hussain

E-Mail Website
Guest Editor
Department of Chemical Engineering, Faculty Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
Interests: advanced and non linear control of process systems; modelling and process control of UF filtration systems to produce clean water; modelling and process control of fuel cell systems; advanced mathematical modelling of gas olefin polymerization in fluidized-bed catalytic reactor; advanced control for semi-active car suspension system; optimisation of chemical process systems; development of software for online process control; artificial intelligence for modelling and control of process systems; process control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wan Ramli Wan Daud

E-Mail Website
Guest Editor
Department of Chemical & Process Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, 436000 UKM Bangi, Malaysia
Interests: engineering & materials science; chemical compounds; physics & astronomy; chemistry and materials; engineering; general; physics

Special Issue Information

Dear Colleagues,

Ever increasing energy consumption, rising public awareness for environmental protection, and higher prices of fossil fuels have motivated many to look for alternative/renewable energy sources. World fossil fluid fuel demand will soon exceed world fossil fluid fuel production, which will be expected to lead to an energy shortage crisis unless a sustainable alternative fuel is available soon. Among the many alternative fuel sources, fuel cells have received the greatest amount of attention, while they can also act as cogeneration systems.

The complicated reaction, heat, and mass transfer mechanisms in the fuel cells introduce extreme nonlinearities in the dynamcis of the fuel cell. The fundamental modeling and control problem in the fuel cells is further complicated by the existence of the strong interaction between the input and output parameters (conventional process modeling and control strategies are incapable of coping with these difficulties). Conventional models do not consider all these the phenomena in their model. Therefore, a comprehensive model is needed to provide a more realistic understanding of the phenomena encountered in fuel cells and improve the quantitative understanding of the actual process.

Since fuel cells are severely nonlinear and typically have several operational constraints, a single linear controller may not provide satisfactory performance over a wide range of operating conditions. Therefore, an efficient advanced process control scheme needs to be implemented due to process dynamic nonlinearities and difficulties involved in the robust control of fuel cells. As such, the modeling and control of fuel cells is a huge challenge for all researchers.

Since the simulation results of modeling are only a prediction and estimation of the real system, an important step in the development of modeling and control is online validation. Unfortunately, there is a lack of experimental validation of the dynamic models of fuel cells in the open literature at present.

Hence, this Special Issue on “Modeling and Control of Fuel Cells” aims to compile together novel advances in the development and application of computational modeling to address these longstanding challenges of these fuel-cell systems. Topics include, but are not limited to, the following:

  • The development of improved modeling methods for fuel cells;
  • The development of advanced systems identification and observers in fuel-cell systems;
  • The development of advanced control strategies for fuel cells;
  • Optimization of the fuel-cell system, especially in cogeneration systems; and
  • Online validation of modeling and control techniques developed for fuel-cell system.

Prof. Dr. Mohd Azlan Hussain
Prof. Dr. Wan Ramli Wan Daud
Guest editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • model
  • control
  • estimator
  • optimized
  • observers
  • validation
  • fuel cells
  • cogeneration system

Published Papers (8 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Editorial

Jump to: Research, Review

2 pages, 157 KiB  
Editorial
Special Issue on “Modelling and Process Control of Fuel Cell Systems”
by Mohd Azlan Hussain and Wan Ramli Wan Daud
Processes 2020, 8(12), 1592; https://doi.org/10.3390/pr8121592 - 3 Dec 2020
Viewed by 1274
Abstract
The ever increasing energy consumption, rising public awareness for environmental protection, and higher prices of fossil fuels have motivated many to look for alternative and renewable energy sources [...] Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)

Research

Jump to: Editorial, Review

12 pages, 1198 KiB  
Article
Air-Forced Flow in Proton Exchange Membrane Fuel Cells: Calculation of Fan-Induced Friction in Open-Cathode Conduits with Virtual Roughness
by Dejan Brkić and Pavel Praks
Processes 2020, 8(6), 686; https://doi.org/10.3390/pr8060686 - 11 Jun 2020
Cited by 6 | Viewed by 2701
Abstract
Measurements of pressure drop during experiments with fan-induced air flow in the open-cathode proton exchange membrane fuel cells (PEMFCs) show that flow friction in its open-cathode side follows logarithmic law similar to Colebrook’s model for flow through pipes. The stable symbolic regression model [...] Read more.
Measurements of pressure drop during experiments with fan-induced air flow in the open-cathode proton exchange membrane fuel cells (PEMFCs) show that flow friction in its open-cathode side follows logarithmic law similar to Colebrook’s model for flow through pipes. The stable symbolic regression model for both laminar and turbulent flow presented in this article correlates air flow and pressure drop as a function of the variable flow friction factor which further depends on the Reynolds number and the virtual roughness. To follow the measured data, virtual inner roughness related to the mesh of conduits of fuel cell used in the mentioned experiment is 0.03086, whereas for pipes, real physical roughness of their inner pipe surface goes practically from 0 to 0.05. Numerical experiments indicate that the novel approximation of the Wright-ω function reduced the computational time from half of a minute to fragments of a second. The relative error of the estimated friction flow factor is less than 0.5%. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

10 pages, 3041 KiB  
Article
Studies on Influence of Cell Temperature in Direct Methanol Fuel Cell Operation
by R. Govindarasu and S. Somasundaram
Processes 2020, 8(3), 353; https://doi.org/10.3390/pr8030353 - 19 Mar 2020
Cited by 21 | Viewed by 3865
Abstract
Directmethanol fuel cells (DMFCs) offer one of the most promising alternatives for the replacement of fossil fuels. A DMFC that had an active Membrane Electrode Assembly (MEA) area of 45 cm2, a squoval-shaped manifold hole design, and a Pt-Ru/C catalyst combination [...] Read more.
Directmethanol fuel cells (DMFCs) offer one of the most promising alternatives for the replacement of fossil fuels. A DMFC that had an active Membrane Electrode Assembly (MEA) area of 45 cm2, a squoval-shaped manifold hole design, and a Pt-Ru/C catalyst combination at the anode was taken for analysis in simulation and real-time experimentation. A mathematical model was developed using dynamic equations of a DMFC. Simulation of a DMFC model using MATLAB software was carried out to identify the most influencing process variables, namely cell temperature, methanol flow rate and methanol concentration during a DMFC operation. Simulation results were recorded and analyzed. It was observed from the results that the cell temperature was the most influencing process variable in the DMFC operation, more so than the methanol flow rate and the methanol concentration. In the DMFC, real-time experimentation was carried out at different cell temperatures to find out the optimum temperature at which maximum power density was obtained. The results obtained in simulation and the experiment were compared and it was concluded that the temperature was the most influencing process variable and 333K was the optimum operating temperature required to achieve the most productive performance in power density of the DMFC. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

13 pages, 2347 KiB  
Article
Simulation of Solid Oxide Fuel Cell Anode in Aspen HYSYS—A Study on the Effect of Reforming Activity on Distributed Performance Profiles, Carbon Formation, and Anode Oxidation Risk
by Khaliq Ahmed, Amirpiran Amiri and Moses O. Tadé
Processes 2020, 8(3), 268; https://doi.org/10.3390/pr8030268 - 27 Feb 2020
Cited by 7 | Viewed by 5324
Abstract
A distributed variable model for solid oxide fuel cell (SOFC), with internal fuel reforming on the anode, has been developed in Aspen HYSYS. The proposed model accounts for the complex and interactive mechanisms involved in the SOFC operation through a mathematically viable and [...] Read more.
A distributed variable model for solid oxide fuel cell (SOFC), with internal fuel reforming on the anode, has been developed in Aspen HYSYS. The proposed model accounts for the complex and interactive mechanisms involved in the SOFC operation through a mathematically viable and numerically fast modeling framework. The internal fuel reforming reaction calculations have been carried out in a plug flow reactor (PFR) module integrated with a spreadsheet module to interactively calculate the electrochemical process details. By interlinking the two modules within Aspen HYSYS flowsheeting environment, the highly nonlinear SOFC distributed profiles have been readily captured using empirical correlations and without the necessity of using an external coding platform, such as MATLAB or FORTRAN. Distributed variables including temperature, current density, and concentration profiles along the cell length, have been discussed for various reforming activity rates. Moreover, parametric estimation of anode oxidation risk and carbon formation potential against fuel reformation intensity have been demonstrated that contributes to the SOFC lifetime evaluation. Incrementally progressive catalyst activity has been proposed as a technically viable approach for attaining smooth profiles within the SOFC anode. The proposed modeling platform paves the way for SOFC system flowsheeting and optimization, particularly where the study of systems with stack distributed variables is of interest. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

16 pages, 1669 KiB  
Article
Design and Implementation of the Off-Line Robust Model Predictive Control for Solid Oxide Fuel Cells
by Narissara Chatrattanawet, Soorathep Kheawhom, Yong-Song Chen and Amornchai Arpornwichanop
Processes 2019, 7(12), 918; https://doi.org/10.3390/pr7120918 - 3 Dec 2019
Cited by 8 | Viewed by 2606
Abstract
An off-line robust linear model predictive control (MPC) using an ellipsoidal invariant set is synthesized based on an uncertain polytopic approach and then implemented to control the temperature and fuel in a direct internal reforming solid oxide fuel cell (SOFC). The state feedback [...] Read more.
An off-line robust linear model predictive control (MPC) using an ellipsoidal invariant set is synthesized based on an uncertain polytopic approach and then implemented to control the temperature and fuel in a direct internal reforming solid oxide fuel cell (SOFC). The state feedback control is derived by minimizing an upper bound on the worst-case performance cost. The simulation results indicate that the synthesized robust MPC algorithm can control and guarantee the stability of the SOFC; although there are uncertainties in some model parameters, it can keep both the temperature and fuel at their setpoints. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Graphical abstract

21 pages, 4428 KiB  
Article
Modeling, Management, and Control of an Autonomous Wind/Fuel Cell Micro-Grid System
by Ibrahem E. Atawi, Ahmed M. Kassem and Sherif A. Zaid
Processes 2019, 7(2), 85; https://doi.org/10.3390/pr7020085 - 8 Feb 2019
Cited by 21 | Viewed by 4564
Abstract
This paper proposes a microelectric power grid that includes wind and fuel cell power generation units, as well as a water electrolyzer for producing hydrogen gas. The grid is loaded by an induction motor (IM) as a dynamic load and constant impedance load. [...] Read more.
This paper proposes a microelectric power grid that includes wind and fuel cell power generation units, as well as a water electrolyzer for producing hydrogen gas. The grid is loaded by an induction motor (IM) as a dynamic load and constant impedance load. An optimal control algorithm using the Mine Blast Algorithm (MBA) is designed to improve the performance of the proposed renewable energy system. Normally, wind power is adapted to feed the loads at normal circumstances. Nevertheless, the fuel cell compensates extra load power demand. An optimal controller is applied to regulate the load voltage and frequency of the main power inverter. Also, optimal vector control is applied to the IM speed control. The response of the microgrid with the proposed optimal control is obtained under step variation in wind speed, load impedance, IM rotor speed, and motor mechanical load torque. The simulation results indicate that the proposed renewable generation system supplies the system loads perfectly and keeps up the desired load demand. Furthermore, the IM speed performance is acceptable under turbulent wind speed. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

14 pages, 2906 KiB  
Article
Environmental Sustainability Assessment of Typical Cathode Materials of Lithium-Ion Battery Based on Three LCA Approaches
by Lei Wang, Haohui Wu, Yuchen Hu, Yajuan Yu and Kai Huang
Processes 2019, 7(2), 83; https://doi.org/10.3390/pr7020083 - 7 Feb 2019
Cited by 18 | Viewed by 5320
Abstract
With the rapid increase in production of lithium-ion batteries (LIBs) and environmental issues arising around the world, cathode materials, as the key component of all LIBs, especially need to be environmentally sustainable. However, a variety of life cycle assessment (LCA) methods increase the [...] Read more.
With the rapid increase in production of lithium-ion batteries (LIBs) and environmental issues arising around the world, cathode materials, as the key component of all LIBs, especially need to be environmentally sustainable. However, a variety of life cycle assessment (LCA) methods increase the difficulty of environmental sustainability assessment. Three authoritative LCAs, IMPACT 2002+, Eco-indicator 99(EI-99), and ReCiPe, are used to assess three traditional marketization cathode materials, compared with a new cathode model, FeF3(H2O)3/C. They all show that four cathode models are ranked by a descending sequence of environmental sustainable potential: FeF3(H2O)3/C, LiFe0.98Mn0.02PO4/C, LiFePO4/C, and LiCoO2/C in total values. Human health is a common issue regarding these four cathode materials. Lithium is the main contributor to the environmental impact of the latter three cathode materials. At the midpoint level in different LCAs, the toxicity and land issues for LiCoO2/C, the non-renewable resource consumption for LiFePO4/C, the metal resource consumption for LiFe0.98Mn0.02PO4/C, and the mineral refinement for FeF3(H2O)3/C show relatively low environmental sustainability. Three LCAs have little influence on total endpoint and element contribution values. However, at the midpoint level, the indicator with the lowest environmental sustainability for the same cathode materials is different in different methodologies. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

Review

Jump to: Editorial, Research

27 pages, 825 KiB  
Review
A Comprehensive Review and Technical Guideline for Optimal Design and Operations of Fuel Cell-Based Cogeneration Systems
by Farah Ramadhani, Mohd Azlan Hussain and Hazlie Mokhlis
Processes 2019, 7(12), 950; https://doi.org/10.3390/pr7120950 - 12 Dec 2019
Cited by 34 | Viewed by 5038
Abstract
The need for energy is increasing from year to year and has to be fulfilled by developing innovations in energy generation systems. Cogeneration is one of the matured technologies in energy generation, which has been implemented since the last decade. Cogeneration is defined [...] Read more.
The need for energy is increasing from year to year and has to be fulfilled by developing innovations in energy generation systems. Cogeneration is one of the matured technologies in energy generation, which has been implemented since the last decade. Cogeneration is defined as energy generation unit that simultaneously produced electricity and heat from a single primary fuel source. Currently, the implementation of this system has been spread over the world for stationary and mobile power generation in residential, industrial and transportation uses. On the other hand, fuel cells as an emerging energy conversion device are potential prime movers for this cogeneration system due to its high heat production and flexibility in its fuel usage. Even though the fuel cell-based cogeneration system has been popularly implemented in research and commercialization sectors, the review regarding this technology is still limited. Focusing on the optimal design of the fuel cell-based cogeneration system, this study attempts to provide a comprehensive review, guideline and future prospects of this technology. With an up-to-date literature list, this review study becomes an important source for researchers who are interested in developing this system for future implementation. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-8
Back to TopTop