A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load
Proton exchange membrane (PEM) fuel cells still suffer from the challenge of limited durability, hindering their widespread commercialization. To overcome this limitation, resorting to Multi-stack Fuel Cell (MFC) systems instead of single fuel cells is a promising solution. Indeed, by optimally dist...
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| Published in | Reliability engineering & system safety Vol. 241; no. January 2024; p. 109660 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2024
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0951-8320 1879-0836 |
| DOI | 10.1016/j.ress.2023.109660 |
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| Abstract | Proton exchange membrane (PEM) fuel cells still suffer from the challenge of limited durability, hindering their widespread commercialization. To overcome this limitation, resorting to Multi-stack Fuel Cell (MFC) systems instead of single fuel cells is a promising solution. Indeed, by optimally distributing the power demand among the different stacks while taking into account their state of health, an efficient Energy Management Strategy (EMS) can be achieved. Here a new multi-stack configuration, based on an oversized multi-stack system is explored. The problem addressed in this paper is to develop a methodology that manages the operation of an oversized three-stack system where only two of them operate simultaneously. The first stage is to predict the deterioration rate of each stack according to the load allocation, and link the deterioration rate of each stack with the load dynamics. To that end, several stochastic deterioration models, from the classical Gamma process model to more complex models with random effects have been developed and tailored to the fuel cell specificities. Then, an event-based decision-making strategy has been established, that determines the load allocations among the operating stacks. This strategy is based on the minimization of the deterioration phenomena due to both the load amplitude and the load variations. Finally, this strategy is extended to the three-stack oversized system by adding the decision to start or stop a stack. These strategies have been validated under random dynamic load profiles, and Monte Carlo simulation results verify the efficiency of the proposed strategies through improved system lifetime.
•Stochastic deterioration model with load-dependent and stack-to-stack variability.•Multi-stack fuel cell system operating under random dynamic load profiles.•Proposition of a deterioration aware energy management strategy.•Joint management of load allocation and switching decisions for multi-stack fuel cells. |
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| AbstractList | Proton exchange membrane (PEM) fuel cells still suffer from the challenge of limited durability, hindering their widespread commercialization. To overcome this limitation, resorting to Multi-stack Fuel Cell (MFC) systems instead of single fuel cells is a promising solution. Indeed, by optimally distributing the power demand among the different stacks while taking into account their state of health, an efficient Energy Management Strategy (EMS) can be achieved. Here a new multi-stack configuration, based on an oversized multi-stack system is explored. The problem addressed in this paper is to develop a methodology that manages the operation of an oversized three-stack system where only two of them operatesimultaneously. The first stage is to predict the deterioration rate of each stack according to the load allocation, and link the deterioration rate of each stack with the load dynamics. To that end, several stochastic deterioration models, from the classical Gamma process model to more complex models with random effects havebeen developed and tailored to the fuel cell specificities. Then, an event-based decision-making strategy has been established, that determines the load allocations among the operating stacks. This strategy is based on the minimization of the deterioration phenomena due to both the load amplitude and the load variations. Finally, this strategy is extended to the three-stack oversized system by adding the decision to start or stop a stack. These strategies have been validated under random dynamic load profiles, and Monte Carlo simulation results verify the efficiency of the proposed strategies through improved system lifetime. Proton exchange membrane (PEM) fuel cells still suffer from the challenge of limited durability, hindering their widespread commercialization. To overcome this limitation, resorting to Multi-stack Fuel Cell (MFC) systems instead of single fuel cells is a promising solution. Indeed, by optimally distributing the power demand among the different stacks while taking into account their state of health, an efficient Energy Management Strategy (EMS) can be achieved. Here a new multi-stack configuration, based on an oversized multi-stack system is explored. The problem addressed in this paper is to develop a methodology that manages the operation of an oversized three-stack system where only two of them operate simultaneously. The first stage is to predict the deterioration rate of each stack according to the load allocation, and link the deterioration rate of each stack with the load dynamics. To that end, several stochastic deterioration models, from the classical Gamma process model to more complex models with random effects have been developed and tailored to the fuel cell specificities. Then, an event-based decision-making strategy has been established, that determines the load allocations among the operating stacks. This strategy is based on the minimization of the deterioration phenomena due to both the load amplitude and the load variations. Finally, this strategy is extended to the three-stack oversized system by adding the decision to start or stop a stack. These strategies have been validated under random dynamic load profiles, and Monte Carlo simulation results verify the efficiency of the proposed strategies through improved system lifetime. •Stochastic deterioration model with load-dependent and stack-to-stack variability.•Multi-stack fuel cell system operating under random dynamic load profiles.•Proposition of a deterioration aware energy management strategy.•Joint management of load allocation and switching decisions for multi-stack fuel cells. |
| ArticleNumber | 109660 |
| Author | Bérenguer, Christophe Zuo, Jian Cadet, Catherine Li, Zhongliang Outbib, Rachid |
| Author_xml | – sequence: 1 givenname: Jian surname: Zuo fullname: Zuo, Jian email: jian.zuo@utbm.fr organization: Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble, 38000, France – sequence: 2 givenname: Catherine surname: Cadet fullname: Cadet, Catherine email: catherine.cadet@grenoble-inp.fr organization: Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble, 38000, France – sequence: 3 givenname: Zhongliang orcidid: 0000-0001-7021-2103 surname: Li fullname: Li, Zhongliang email: zhongliang.li@univ-fcomte.fr organization: Université de Franche-Comté, UTBM, CNRS, Institut FEMTO-ST, 90000, Belfort, France – sequence: 4 givenname: Christophe surname: Bérenguer fullname: Bérenguer, Christophe email: christophe.berenguer@grenoble-inp.fr organization: Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble, 38000, France – sequence: 5 givenname: Rachid surname: Outbib fullname: Outbib, Rachid email: Rachid.Outbib@lis-lab.fr organization: LIS Laboratory, Aix-Marseille University, Marseille, 13397, France |
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| Issue | January 2024 |
| Keywords | Multi-stack fuel cells Stochastic deterioration Health-aware energy management strategies Random dynamic load profile Multi-stack fuel cells, Stochastic deterioration, Random dynamic load profile, Health-aware energy management strategies |
| Language | English |
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hybrid electric vehicle |
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| Snippet | Proton exchange membrane (PEM) fuel cells still suffer from the challenge of limited durability, hindering their widespread commercialization. To overcome this... |
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| SubjectTerms | Automatic Electric power Engineering Sciences Fluid mechanics Health-aware energy management strategies Mechanics Multi-stack fuel cells Physics Random dynamic load profile Stochastic deterioration Thermics |
| Title | A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load |
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