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High efficiency thermoelectric cooperative control of a stand-alone solid oxide fuel cell system with an air bypass valve

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  • Jiang, Jianhua
  • Shen, Tan
  • Deng, Zhonghua
  • Fu, Xiaowei
  • Li, Jian
  • Li, Xi

Abstract

Power tracking, thermal management and system efficiency optimization are three key issues of ensuring high performance and long life time for a SOFC system from the view of practical application. In this paper, a novel control strategy is proposed to cooperatively manage the three competitive issues by maintaining thermal constraints and optimizing system efficiency while conducting fast load tracking. Firstly, a validated high fidelity SOFC system model incorporating a one-dimensional stack model is constructed according to physical laws and chemical kinetics. With this model, we have conducted in-depth system analysis and calculated optimal operating points (OOPs) for different power outputs, and then found the mechanism for efficiency optimization. By transient analysis of OOPs based power switching process, a thermo-electric decoupling method and systematic thermos-electrical cooperative controlling strategy are proposed. The control strategy includes two sub-controllers, one is an OOPs based feed-forward controller for thermal management, and the other is Takagi-Sugeno (TS) fuzzy model based constrained generalized predictive control (CGPC) controller for power tracking, input constraint handling and fuel starvation prevention. By applying this control strategy, the system efficiency can be improved to 43–53% during fast power tracking and temperature constraining can be guaranteed.

Suggested Citation

  • Jiang, Jianhua & Shen, Tan & Deng, Zhonghua & Fu, Xiaowei & Li, Jian & Li, Xi, 2018. "High efficiency thermoelectric cooperative control of a stand-alone solid oxide fuel cell system with an air bypass valve," Energy, Elsevier, vol. 152(C), pages 13-26.
  • Handle: RePEc:eee:energy:v:152:y:2018:i:c:p:13-26
    DOI: 10.1016/j.energy.2018.02.100
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    References listed on IDEAS

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    Cited by:

    1. Cheng, Tianliang & Jiang, Jianhua & Wu, Xiaodong & Li, Xi & Xu, Mengxue & Deng, Zhonghua & Li, Jian, 2019. "Application oriented multiple-objective optimization, analysis and comparison of solid oxide fuel cell systems with different configurations," Applied Energy, Elsevier, vol. 235(C), pages 914-929.
    2. Hongchuan Qin & Zhonghua Deng & Xi Li, 2022. "Cooperative Control of a Steam Reformer Solid Oxide Fuel Cell System for Stable Reformer Operation," Energies, MDPI, vol. 15(9), pages 1-14, May.
    3. Jiang, Jianhua & Zhou, Renjie & Xu, Hao & Wang, Hao & Wu, Ping & Wang, Zhuo & Li, Jian, 2022. "Optimal sizing, operation strategy and case study of a grid-connected solid oxide fuel cell microgrid," Applied Energy, Elsevier, vol. 307(C).
    4. Jie, Hao & Liao, Jiawei & Zhu, Guozhu & Hong, Weirong, 2024. "Nonlinear model predictive control of direct internal reforming solid oxide fuel cells via PDAE-constrained dynamic optimization," Applied Energy, Elsevier, vol. 360(C).
    5. Wu, Xiao-long & Xu, Yuan-wu & Zhao, Dong-qi & Zhong, Xiao-bo & Li, Dong & Jiang, Jianhua & Deng, Zhonghua & Fu, Xiaowei & Li, Xi, 2020. "Extended-range electric vehicle-oriented thermoelectric surge control of a solid oxide fuel cell system," Applied Energy, Elsevier, vol. 263(C).
    6. Jingxuan Peng & Dongqi Zhao & Yuanwu Xu & Xiaolong Wu & Xi Li, 2023. "Comprehensive Analysis of Solid Oxide Fuel Cell Performance Degradation Mechanism, Prediction, and Optimization Studies," Energies, MDPI, vol. 16(2), pages 1-23, January.
    7. Vitale, F. & Rispoli, N. & Sorrentino, M. & Rosen, M.A. & Pianese, C., 2021. "On the use of dynamic programming for optimal energy management of grid-connected reversible solid oxide cell-based renewable microgrids," Energy, Elsevier, vol. 225(C).
    8. Zhong, Xiaobo & Xu, Yuanwu & Liu, Yanlin & Wu, Xiaolong & Zhao, Dongqi & Zheng, Yi & Jiang, Jianhua & Deng, Zhonghua & Fu, Xiaowei & Li, Xi, 2020. "Root cause analysis and diagnosis of solid oxide fuel cell system oscillations based on data and topology-based model," Applied Energy, Elsevier, vol. 267(C).

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