IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v241y2024ics0951832023005744.html
   My bibliography  Save this article

A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load

Author

Listed:
  • Zuo, Jian
  • Cadet, Catherine
  • Li, Zhongliang
  • Bérenguer, Christophe
  • Outbib, Rachid

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.

Suggested Citation

  • Zuo, Jian & Cadet, Catherine & Li, Zhongliang & Bérenguer, Christophe & Outbib, Rachid, 2024. "A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    • Handle: RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023005744
    DOI: 10.1016/j.ress.2023.109660
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023005744
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109660?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tsoumpris, Charalampos & Theotokatos, Gerasimos, 2023. "A decision-making approach for the health-aware energy management of ship hybrid power plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Song, Kai & Cui, Lirong, 2022. "A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    3. Gargari, Milad Zamani & Hagh, Mehrdad Tarafdar & Zadeh, Saeid Ghassem, 2021. "Preventive maintenance scheduling of multi energy microgrid to enhance the resiliency of system," Energy, Elsevier, vol. 221(C).
    4. Zhou, Su & Fan, Lei & Zhang, Gang & Gao, Jianhua & Lu, Yanda & Zhao, Peng & Wen, Chaokai & Shi, Lin & Hu, Zhe, 2022. "A review on proton exchange membrane multi-stack fuel cell systems: architecture, performance, and power management," Applied Energy, Elsevier, vol. 310(C).
    5. Salem, Marwa Belhaj & Fouladirad, Mitra & Deloux, Estelle, 2022. "Variance Gamma process as degradation model for prognosis and imperfect maintenance of centrifugal pumps," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Wu, Bei & Ding, Dong, 2022. "A gamma process based model for systems subject to multiple dependent competing failure processes under Markovian environments," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    7. Zio, Enrico, 2022. "Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    9. Zhou, Su & Zhang, Gang & Fan, Lei & Gao, Jianhua & Pei, Fenglai, 2022. "Scenario-oriented stacks allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 308(C).
    10. Hu, Yang & Miao, Xuewen & Si, Yong & Pan, Ershun & Zio, Enrico, 2022. "Prognostics and health management: A review from the perspectives of design, development and decision," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    11. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    12. Herr, Nathalie & Nicod, Jean-Marc & Varnier, Christophe & Jardin, Louise & Sorrentino, Antonella & Hissel, Daniel & Péra, Marie-Cécile, 2017. "Decision process to manage useful life of multi-stacks fuel cell systems under service constraint," Renewable Energy, Elsevier, vol. 105(C), pages 590-600.
    13. Vasilyev, A. & Andrews, J. & Dunnett, S.J. & Jackson, L.M., 2021. "Dynamic Reliability Assessment of PEM Fuel Cell Systems," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liang, Qingzhu & Yang, Yinghao & Peng, Changhong, 2023. "A reliability model for systems subject to mutually dependent degradation processes and random shocks under dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Zheng, Rui & Najafi, Seyedvahid & Zhang, Yingzhi, 2022. "A recursive method for the health assessment of systems using the proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Ma, Jie & Cai, Li & Liao, Guobo & Yin, Hongpeng & Si, Xiaosheng & Zhang, Peng, 2023. "A multi-phase Wiener process-based degradation model with imperfect maintenance activities," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    4. Aizpurua, J.I. & Stewart, B.G. & McArthur, S.D.J. & Penalba, M. & Barrenetxea, M. & Muxika, E. & Ringwood, J.V., 2022. "Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Zhang, Gang & Zhou, Su & Gao, Jianhua & Fan, Lei & Lu, Yanda, 2023. "Stacks multi-objective allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 331(C).
    6. Zhou, Su & Xie, Zhengchun & Chen, Chunguang & Zhang, Gang & Guo, Junhua, 2022. "Design and energy consumption research of an integrated air supply device for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 324(C).
    7. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    8. Meng, Huixing & Liu, Xuan & Xing, Jinduo & Zio, Enrico, 2022. "A method for economic evaluation of predictive maintenance technologies by integrating system dynamics and evolutionary game modelling," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    9. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    10. Meng, Huixing & Geng, Mengyao & Xing, Jinduo & Zio, Enrico, 2022. "A hybrid method for prognostics of lithium-ion batteries capacity considering regeneration phenomena," Energy, Elsevier, vol. 261(PB).
    11. Compare, Michele & Antonello, Federico & Pinciroli, Luca & Zio, Enrico, 2022. "A general model for life-cycle cost analysis of Condition-Based Maintenance enabled by PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    12. Han, Te & Li, Yan-Fu, 2022. "Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    13. Zhang, Nan & Deng, Yingjun & Liu, Bin & Zhang, Jun, 2023. "Condition-based maintenance for a multi-component system in a dynamic operating environment," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    14. Zou, Xinyu & Tao, Laifa & Sun, Lulu & Wang, Chao & Ma, Jian & Lu, Chen, 2023. "A case-learning-based paradigm for quantitative recommendation of fault diagnosis algorithms: A case study of gearbox," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    15. Zhang, Wei-Heng & Qin, Jianjun & Lu, Da-Gang & Liu, Min & Faber, Michael H., 2023. "Quantification of the value of condition monitoring system with time-varying monitoring performance in the context of risk-based inspection," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    16. Dai, Xinliang & Qu, Sheng & Sui, Hao & Wu, Pingbo, 2022. "Reliability modelling of wheel wear deterioration using conditional bivariate gamma processes and Bayesian hierarchical models," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    17. Hao, Xinyang & Salhi, Issam & Laghrouche, Salah & Ait Amirat, Youcef & Djerdir, Abdesslem, 2023. "Multiple inputs multi-phase interleaved boost converter for fuel cell systems applications," Renewable Energy, Elsevier, vol. 204(C), pages 521-531.
    18. Zhou, Su & Fan, Lei & Zhang, Gang & Gao, Jianhua & Lu, Yanda & Zhao, Peng & Wen, Chaokai & Shi, Lin & Hu, Zhe, 2022. "A review on proton exchange membrane multi-stack fuel cell systems: architecture, performance, and power management," Applied Energy, Elsevier, vol. 310(C).
    19. Lee, Juseong & Mitici, Mihaela, 2023. "Deep reinforcement learning for predictive aircraft maintenance using probabilistic Remaining-Useful-Life prognostics," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    20. He, Yuxuan & Su, Huai & Zio, Enrico & Peng, Shiliang & Fan, Lin & Yang, Zhaoming & Yang, Zhe & Zhang, Jinjun, 2023. "A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:241:y:2024:i:c:s0951832023005744. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.