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Advanced Diagnostics, Prognostics, and Control of Fuel Cell Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 7866

Special Issue Editors


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Guest Editor
Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, Italy
Interests: fuel cells; electrolysers; energy systems; hybrid vehicles; modeling; optimization; diagnostics; prognostics; control
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E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Salerno, Italy
Interests: internal combustion engines; energy management; emissions reduction; fuel cells; hybrid vehicles; energy systems; optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The mass market deployment of fuel cell systems, based on either Polymer Electrolyte Membrane Fuel Cell (PEMFC) or Solid Oxide Fuel Cell (SOFC) technologies, is currently fostered thanks to their increasing durability and availability with respect to conventional energy systems. A key role in this improvement is related to the implementation of advanced diagnostic, prognostic, and control strategies that suitably combines information coming from system models and sensors as well as experts and historical knowledge. Therefore, this Special Issue of the Energies journal aims at collecting the most up-to-date advancements concerning research and innovation on diagnostics, prognostics, and control of fuel cell systems. The main topics of interests are related (but not limited to):

  • Design and application of diagnostic algorithms for fuel cell systems;
  • Management and optimization of fuel cell system operation;
  • Optimal control of fuel cell systems;
  • Advanced prognostics and durability estimation of fuel cell systems;
  • Mitigation strategies applied to fuel cell systems;
  • Design and application of predictive maintenance related to fuel cell systems;
  • Integration of advanced control with diagnostic and prognostics information for fuel cell systems.

Dr. Pierpaolo Polverino
Prof. Dr. Cesare Pianese
Guest Editors

Manuscript Submission Information

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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. Energies is an international peer-reviewed open access semimonthly 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 2600 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

  • Proton Exchange Membrane Fuel Cell (PEMFC)
  • Solid Oxide Fuel Cell (SOFC)
  • Diagnostics
  • Prognostics
  • Control
  • Optimization
  • Prognostics and Health Management (PHM)
  • Remaining Useful Life (RUL)
  • Predictive Maintenance
  • Mitigation strategies
  • Durability
  • Availability

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Published Papers (3 papers)

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Research

19 pages, 4210 KiB  
Article
Optimal Design and Operation of Dual-Ejector PEMFC Hydrogen Supply and Circulation System
by Li Chen, Keda Xu, Zuyong Yang, Zhen Yan and Zuomin Dong
Energies 2022, 15(15), 5427; https://doi.org/10.3390/en15155427 - 27 Jul 2022
Cited by 22 | Viewed by 3337
Abstract
A proton exchange membrane fuel cell (PEMFC) system requires an adequate hydrogen supply and circulation to achieve its expected performance and operating life. An ejector-based hydrogen circulation system can reduce the operating and maintenance costs, noise, and parasitic power consumption by eliminating the [...] Read more.
A proton exchange membrane fuel cell (PEMFC) system requires an adequate hydrogen supply and circulation to achieve its expected performance and operating life. An ejector-based hydrogen circulation system can reduce the operating and maintenance costs, noise, and parasitic power consumption by eliminating the recirculation pump. However, the ejector’s hydrogen entrainment capability, restricted by its geometric parameters and flow control variability, can only operate properly within a relatively narrow range of fuel cell output power. This research introduced the optimal design and operation control methods of a dual-ejector hydrogen supply/circulation system to support the full range of PEMFC system operations. The technique was demonstrated on a 70 kW PEMFC stack with an effective hydrogen entrainment ratio covering 8% to 100% of its output power. The optimal geometry design ensured each ejector covered a specific output power range with maximized entrainment capability. Furthermore, the optimal control of hydrogen flow and the two ejectors’ opening and closing times minimized the anode gas pressure fluctuation and reduced the potential harm to the PEMFC’s operation life. The optimizations were based on dedicated computational fluid dynamics (CFD) and system dynamics models and simulations. Bench tests of the resulting ejector-based hydrogen supply/circulation system verified the simulation and optimization results. Full article
(This article belongs to the Special Issue Advanced Diagnostics, Prognostics, and Control of Fuel Cell Systems)
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17 pages, 534 KiB  
Article
Fast Model Predictive Control of PEM Fuel Cell System Using the L1 Norm
by Robert Nebeluk and Maciej Ławryńczuk
Energies 2022, 15(14), 5157; https://doi.org/10.3390/en15145157 - 15 Jul 2022
Cited by 6 | Viewed by 1747
Abstract
This work describes the development of a fast Model Predictive Control (MPC) algorithm for a Proton Exchange Membrane (PEM) fuel cell. The MPC cost-function used considers the sum of absolute values of predicted control errors (the L1 norm). Unlike previous approaches to [...] Read more.
This work describes the development of a fast Model Predictive Control (MPC) algorithm for a Proton Exchange Membrane (PEM) fuel cell. The MPC cost-function used considers the sum of absolute values of predicted control errors (the L1 norm). Unlike previous approaches to nonlinear MPC-L1, in which quite complicated neural approximators have been used, two analytical approximators of the absolute value function are utilised. An advanced trajectory linearisation is performed on-line. As a result, an easy-to-solve quadratic optimisation task is derived. All implementation details of the discussed algorithm are detailed for two considered approximators. Furthermore, the algorithm is thoroughly compared with the classical MPC-L2 method in which the sum of squared predicted control errors is minimised. A multi-criteria control quality assessment is performed as the MPC-L1 and MPC-L2 algorithms are compared using four control quality indicators. It is shown that the presented MPC-L1 scheme gives better results for the PEM. Full article
(This article belongs to the Special Issue Advanced Diagnostics, Prognostics, and Control of Fuel Cell Systems)
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18 pages, 6690 KiB  
Article
Multi-Criteria Optimal Design for FUEL Cell Hybrid Power Sources
by Adriano Ceschia, Toufik Azib, Olivier Bethoux and Francisco Alves
Energies 2022, 15(9), 3364; https://doi.org/10.3390/en15093364 - 5 May 2022
Cited by 8 | Viewed by 2013
Abstract
This paper presents the development of a global and integrated sizing approach under different performance indexes applied to fuel cell/battery hybrid power systems. The strong coupling between the hardware sizing process and the system supervision (energy management strategy EMS) makes it hard for [...] Read more.
This paper presents the development of a global and integrated sizing approach under different performance indexes applied to fuel cell/battery hybrid power systems. The strong coupling between the hardware sizing process and the system supervision (energy management strategy EMS) makes it hard for the design to consider all the possibilities, and today’s methodologies are mostly experience-based approaches that are impervious to technological disruption. With a smart design approach, new technologies are easier to consider, and this approach facilitates the use of new technologies for transport applications with a decision help tool. An automotive application with a hybrid fuel cell (PEMFC)/battery (Li-Ion) is considered to develop this approach. The proposed approach is based on imbricated optimization loops and considers multiple criteria such as the fuel consumption, reliability, and volume of the architecture, in keeping with industry expectations to allow a good trade-off between different performance indexes and explore their design options. This constitutes a low computational time and a very effective support tool that allows limited overconsumption and lifetime reduction for designed architecture in extreme and non-optimal use. We obtain, thanks to this work, a pre-design tool that helps to realize the first conception choice. Full article
(This article belongs to the Special Issue Advanced Diagnostics, Prognostics, and Control of Fuel Cell Systems)
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