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Improved efficiency maximization strategy for vehicular dual-stack fuel cell system considering load state of sub-stacks through predictive soft-loading

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  • Zhang, Caizhi
  • Zeng, Tao
  • Wu, Qi
  • Deng, Chenghao
  • Chan, Siew Hwa
  • Liu, Zhixiang

Abstract

The durability of vehicular fuel cells can be affected by severe load conditions, such as ultrafast loading, frequent start/stop and idling/open-circuit operation. Currently, some fuel cell systems are developed based on dual-stack configuration. For dual-stack systems, not only the system efficiency, but also the load state of sub-stacks is crucial when determining the power distribution between sub-stacks. This study proposes an improved overall efficiency maximization strategy (I-OEMS) that combines a predictive soft-loading method to improve the load state of sub-stacks while ensuring the approximate maximum efficiency. Firstly, a conventional overall efficiency maximization strategy (C-OEMS) is formulated to analyze the load state and possible degradations of sub-stacks under dynamic driving cycles. Then, the proposed I-OEMS is developed accordingly, in which the short-term reference power of sub-stacks is pre-planned according to look-ahead vehicular demand power predicted by an iterative learning framework. Finally, simulations are conducted to analyze the effectiveness. The results show that I-OEMS can effectively limit the loading speed, reduce the start/stop frequency, and operate the auxiliary sub-stack away from idling/open-circuit, so as to enhance the durability. Furthermore, it achieves a better fuel economy compared with simply limiting the loading rate of sub-stacks under C-OEMS, especially for urban driving cycles.

Suggested Citation

  • Zhang, Caizhi & Zeng, Tao & Wu, Qi & Deng, Chenghao & Chan, Siew Hwa & Liu, Zhixiang, 2021. "Improved efficiency maximization strategy for vehicular dual-stack fuel cell system considering load state of sub-stacks through predictive soft-loading," Renewable Energy, Elsevier, vol. 179(C), pages 929-944.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:929-944
    DOI: 10.1016/j.renene.2021.07.090
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    References listed on IDEAS

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    Cited by:

    1. Duan, Hao & Zhang, Caizhi & Wang, Gucheng & Chen, Yu'an & Liu, Zhixiang & Xie, Xianshu & Shuai, Qi, 2022. "Experimental study of the dynamic and transient characteristics of sub-health fuel cell multi-stack systems without DC/DC," Energy, Elsevier, vol. 238(PC).
    2. 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.
    3. Tri-Cuong Do & Hoai-An Trinh & Kyoung-Kwan Ahn, 2023. "Hierarchical Control Strategy with Battery Dynamic Consideration for a Dual Fuel Cell/Battery Tramway," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    4. 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).
    5. Hu, Jianjun & Wang, Yangguang & Zou, Lingbo & Wang, Zhouxin, 2023. "Adaptive rule control strategy for composite energy storage fuel cell vehicle based on vehicle operating state recognition," Renewable Energy, Elsevier, vol. 204(C), pages 166-175.

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