Issue
Sci. Tech. Energ. Transition
Volume 80, 2025
Innovative Strategies and Technologies for Sustainable Renewable Energy and Low-Carbon Development
Article Number 5
Number of page(s) 14
DOI https://doi.org/10.2516/stet/2024098
Published online 06 January 2025
  • Zou T., Guo P., Li F., Wu Q. (2024) Research topic identification and trend prediction of China’s energy policy: A combined LDA-ARIMA approach, Renew. Energy 220, 119619. [CrossRef] [Google Scholar]
  • Jiang B., Raza M.Y. (2023) Research on China’s renewable energy policies under the dual carbon goals: A political discourse analysis, Energy Strat. Rev. 48, 101118. [CrossRef] [Google Scholar]
  • Chamandoust H., Derakhshan G., Hakimi S.M., Bahramara S. (2020) Tri-objective scheduling of residential smart electrical distribution grids with optimal joint of responsive loads with renewable energy sources, J. Energy Storage 27, 101112. [CrossRef] [Google Scholar]
  • Xue D., Shao Z. (2024) Patent text mining based hydrogen energy technology evolution path identification, Int. J. Hydrogen Energy 49, 699–710. [CrossRef] [Google Scholar]
  • Hu D., Wang Y., Li J., Yang Q., Wang J. (2021) Investigation of optimal operating temperature for the PEMFC and its tracking control for energy saving in vehicle applications, Energy Convers. Manage. 249, 114842. [CrossRef] [Google Scholar]
  • Xiao C., Wang B., Wang C., Yan Y. (2023) Design of a novel fully-active PEMFC-Lithium battery hybrid power system based on two automatic ON/OFF switches for unmanned aerial vehicle applications, Energy Convers. Manage 292, 117417. [CrossRef] [Google Scholar]
  • Shahverdian M.H., Sohani A., Pedram M.Z., Sayyaadi H. (2023) An optimal strategy for application of photovoltaic-wind turbine with PEMEC-PEMFC hydrogen storage system based on techno-economic, environmental, and availability indicators, J. Clean. Prod. 384, 135499. [CrossRef] [Google Scholar]
  • Zhang C., Hu H., Ji J., Liu K., Xia X., Nazir M.S., Peng T. (2023) An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC, Appl. Energy 330, 120333. [CrossRef] [Google Scholar]
  • Prigent M. (1997) On board hydrogen generation for fuel cell powered electric cars. A review of various available techniques, Revue de l’Institut Français du Pétrole 52, 349–360. [Google Scholar]
  • Chen D., Xu Y., Tade M.O., Shao Z. (2017) General regulation of air flow distribution characteristics within planar solid oxide fuel cell stacks, ACS Energy Lett. 2, 319–326. [CrossRef] [Google Scholar]
  • Chen D., Ding K., Chen Z., Wei T., Liu K. (2018) Physics field distributions within fuel cell stacks with manifolds penetrating through the plane zone and open outlet features, Energy Convers. Manage. 178, 190–199. [CrossRef] [Google Scholar]
  • Wang W., Liu J., Serbin S., Chen D., Zhou H. (2022) Thermal stress analysis for a typical planar anode-supported fuel cell stack, Sustain. Energy Technol. Assess. 54, 102891. [Google Scholar]
  • Chen D., Zhu Y., Han S., Anatoly L., Andrey M., Lu L. (2023) Investigate the effect of a parallel-cylindrical flow field on the solid oxide fuel cell stack performance by 3D multiphysics simulating, J. Energy Storage 60, 106587. [CrossRef] [Google Scholar]
  • Pukrushpan J.T. (2003) Modeling and control of PEM fuel cell systems and fuel processors, Ph.D. Dissertation, University of Michigan. [Google Scholar]
  • Damour C., Benne M., Lebreton C., Deseure J., Grondin-Perez B. (2014) Real-time implementation of a neural model-based self-tuning PID strategy for oxygen stoichiometry control in PEM fuel cell, Inter. J. Hydrogen Energy 39, 12819–12825. [CrossRef] [Google Scholar]
  • Baroud Z., Benmiloud M., Benalia A., Ocampo-Martinez C. (2017) Novel hybrid fuzzy-PID control scheme for air supply in PEM fuel-cell-based systems, Int. J. Hydrogen Energy 42, 10435–10447. [CrossRef] [Google Scholar]
  • Afsharinejad A., Asemani M.H., Dehghani M. (2020) Optimal linear parameter varying controller design for proton exchange membrane fuel cell using LMI techniques, in: 2020 28th Iranian Conference on Electrical Engineering (ICEE), IEEE, pp. 1–5. [Google Scholar]
  • Zhu Y., Xie Y., Zou J., Li S. (2019) Near-optimal control of net output power for PEMFC system, in: 2019 American Control Conference (ACC), pp. 2801–2806. [CrossRef] [Google Scholar]
  • Ziogou C., Voutetakis S., Georgiadis M.C., Papadopoulou S. (2018) Model predictive control (MPC) strategies for PEM fuel cell systems – A comparative experimental demonstration, Chem. Eng. Res. Des. 131, 656–670. [CrossRef] [Google Scholar]
  • Wang Y., Li H., Feng H., Han K., He S., Gao M. (2021) Simulation study on the PEMFC oxygen starvation based on the coupling algorithm of model predictive control and PID, Energy Convers. Manage. 249, 114851. [CrossRef] [Google Scholar]
  • Napole C., Derbeli M., Barambones O. (2021) A global integral terminal sliding mode control based on a novel reaching law for a proton exchange membrane fuel cell system, Appl. Energy 301, 117473. [CrossRef] [Google Scholar]
  • Abbaker A. M. O., Wang H., Tian Y. (2022) Adaptive integral type‐terminal sliding mode control for PEMFC air supply system using time delay estimation algorithm, Asian J. Control 24, 217–226. [CrossRef] [Google Scholar]
  • Yildirim B., Gheisarnejad M., Özdemir M.T., Khooban M.H. (2024) Multi-agent fuzzy Q-learning-based PEM fuel cell air-feed system control, Int. J. Hydrogen Energy 75, 354–362. [CrossRef] [Google Scholar]
  • Li J., Yu T. (2021) Intelligent controller based on distributed deep reinforcement learning for PEMFC air supply system, IEEE Access 9, 7496–7507. [CrossRef] [Google Scholar]
  • Su Q., Zhou J., Yi F., Hu D., Lu D., Wu G., Zhang C., Deng B., Cao D. (2024) An intelligent control method for PEMFC air supply subsystem to optimize dynamic response performance, Fuel 361, 130697. [CrossRef] [MathSciNet] [Google Scholar]
  • Zhang H.K., Wang Y.F., Wang D.H., Wang Y.L. (2020) Adaptive robust control of oxygen excess ratio for PEMFC system based on type-2 fuzzy logic system, Inform. Sci. 511, 1–17. [CrossRef] [MathSciNet] [Google Scholar]
  • Chamandoust H., Derakhshan G., Bahramara S. (2020) Multi-objective performance of smart hybrid energy system with Multi-optimal participation of customers in day-ahead energy market, Energy Build. 216, 109964. [CrossRef] [Google Scholar]
  • Chamandoust H., Derakhshan G., Hakimi S.M., Bahramara S. (2019) Tri-objective optimal scheduling of smart energy hub system with schedulable loads, J. Clean. Prod. 236, 117584. [CrossRef] [Google Scholar]
  • Chamandoust H., Bahramara S., Derakhshan G. (2020) Day-ahead scheduling problem of smart micro-grid with high penetration of wind energy and demand side management strategies, Sustain. Energy Technol. Assess. 40, 100747. [Google Scholar]
  • Askar S., Sadikova A., Mohammed R.J., Khalaf H.H., Ghazaly N.M., Radhan R.P., Candra O.C. (2024) Optimal demand management of smart energy hybrid system based on multi-objective optimization problem, Sci. Tech. Energ. Trans. 79, 53. [CrossRef] [Google Scholar]
  • Yang L., Zeng T., Yu Q. (2023) Cascade control method of sliding mode and PID for PEMFC air supply system, Energies 16, 228. [Google Scholar]
  • Zhang X., Zhang C., Zhang Z., Gao S., Li H. (2024) Coordinated management of oxygen excess ratio and cathode pressure for PEMFC based on synthesis variable-gain robust predictive control, Appl. Energy 367, 123415. [CrossRef] [Google Scholar]
  • Li J., Yu T., Yang B. (2021) Coordinated control of gas supply system in PEMFC based on multi-agent deep reinforcement learning. Int. J. Hydrogen Energy 46, 33899–33914. [CrossRef] [Google Scholar]
  • Song D., Wu Q., Zeng X., Zhang X., Qian Q., Yang D. (2024) Feedback-linearization decoupling based coordinated control of air supply and thermal management for vehicular fuel cell system. Energy 305, 132347. [CrossRef] [Google Scholar]
  • Feng Y., Yu X., Man Z. (2002) Non-singular terminal sliding mode control of rigid manipulators, Automatica 38, 2159–2167. [CrossRef] [Google Scholar]
  • Pan M., Li C., Liao J., Lei H., Pan C., Meng X., Huang H. (2020) Design and modeling of PEM fuel cell based on different flow fields, Energy 207, 118331. [CrossRef] [Google Scholar]
  • Perrin J.C., Kaddouri A.E., Guendouz L., Mrad C., Mozet K., Dillet J., Leclerc S., Lottin O. (2024) NMR contributions to the study of water transfer in proton exchange membranes for fuel cells, Sci. Tech. Energ. Trans. 79, 21. [CrossRef] [Google Scholar]
  • Yang D., Pan R., Wang Y., Chen Z. (2019) Modeling and control of PEMFC air supply system based on T-S fuzzy theory and predictive control, Energy 188, 116078. [CrossRef] [Google Scholar]

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