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Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle

Author

Listed:
  • Gong, Zhichao
  • Wang, Bowen
  • Xu, Yifan
  • Ni, Meng
  • Gao, Qingchen
  • Hou, Zhongjun
  • Cai, Jun
  • Gu, Xin
  • Yuan, Xinjie
  • Jiao, Kui

Abstract

In this study, an adaptive optimization matching method of the air supply is developed to maintain the high-efficiency operation of the automotive polymer electrolyte membrane fuel cell (PEMFC) system in the life cycle. A 1-D non-isothermal model of the PEMFC stack with 150 kW designed power and a centrifugal air compressor model are developed, considering the fuel cell performance degradation. The genetic algorithm (GA) is used to optimize the overall system efficiency under various output powers to achieve adaptive matching. The 1-D stack model is validated with the experimental test results at two states (before and after 800 h degradation), considering the effect of degradation on the matching strategies. Through the optimization method, the centrifugal air compressor is adaptively matched with the stack of the proposed two states to develop the compressor matching strategies under various stack conditions individually. It is found that the efficiency of the system with this optimized method is 3.8% higher than that of the system without an optimized method under the full system power range. In addition, the new matching strategy between the air compressor and the stack after degradation is exploited by the adaptive optimization method. With the help of this method, the efficiencies of the system and the stack are 5.7% and 2.9% higher than that of the matching strategy without adaptive updating. It is shown that this adaptive optimization method not only improves the output efficiency of the stack but also reduces the additional parasitic power consumed by the compressor.

Suggested Citation

  • Gong, Zhichao & Wang, Bowen & Xu, Yifan & Ni, Meng & Gao, Qingchen & Hou, Zhongjun & Cai, Jun & Gu, Xin & Yuan, Xinjie & Jiao, Kui, 2022. "Adaptive optimization strategy of air supply for automotive polymer electrolyte membrane fuel cell in life cycle," Applied Energy, Elsevier, vol. 325(C).
    • Handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011084
    DOI: 10.1016/j.apenergy.2022.119839
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    References listed on IDEAS

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    1. Benaggoune, Khaled & Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine, 2022. "A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 313(C).
    2. Song, Ke & Ding, Yuhang & Hu, Xiao & Xu, Hongjie & Wang, Yimin & Cao, Jing, 2021. "Degradation adaptive energy management strategy using fuel cell state-of-health for fuel economy improvement of hybrid electric vehicle," Applied Energy, Elsevier, vol. 285(C).
    3. Kui Jiao & Jin Xuan & Qing Du & Zhiming Bao & Biao Xie & Bowen Wang & Yan Zhao & Linhao Fan & Huizhi Wang & Zhongjun Hou & Sen Huo & Nigel P. Brandon & Yan Yin & Michael D. Guiver, 2021. "Designing the next generation of proton-exchange membrane fuel cells," Nature, Nature, vol. 595(7867), pages 361-369, July.
    4. Hou, Junbo & Yang, Min & Ke, Changchun & Zhang, Junliang, 2020. "Control logics and strategies for air supply in PEM fuel cell engines," Applied Energy, Elsevier, vol. 269(C).
    5. Chen, Hong & Zhan, Zhigang & Jiang, Panxing & Sun, Yahao & Liao, Liwen & Wan, Xiongbiao & Du, Qing & Chen, Xiaosong & Song, Hao & Zhu, Ruijie & Shu, Zhanhong & Li, Shang & Pan, Mu, 2022. "Whole life cycle performance degradation test and RUL prediction research of fuel cell MEA," Applied Energy, Elsevier, vol. 310(C).
    6. Yang, Zirong & Du, Qing & Jia, Zhiwei & Yang, Chunguang & Xuan, Jin & Jiao, Kui, 2019. "A comprehensive proton exchange membrane fuel cell system model integrating various auxiliary subsystems," Applied Energy, Elsevier, vol. 256(C).
    7. Li, Bing & Wan, Kechuang & Xie, Meng & Chu, Tiankuo & Wang, Xiaolei & Li, Xiang & Yang, Daijun & Ming, Pingwen & Zhang, Cunman, 2022. "Durability degradation mechanism and consistency analysis for proton exchange membrane fuel cell stack," Applied Energy, Elsevier, vol. 314(C).
    8. Sun, Li & Shen, Jiong & Hua, Qingsong & Lee, Kwang Y., 2018. "Data-driven oxygen excess ratio control for proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 231(C), pages 866-875.
    9. Yin, Cong & Song, Yating & Liu, Meiru & Gao, Yan & Li, Kai & Qiao, Zemin & Tang, Hao, 2022. "Investigation of proton exchange membrane fuel cell stack with inversely phased wavy flow field design," Applied Energy, Elsevier, vol. 305(C).
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