IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v325y2022ics0306261922011084.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922011084
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119839?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. 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. 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).
    3. 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).
    4. 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.
    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. 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.
    7. 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).
    8. 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).
    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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lopez-Juarez, M. & Rockstroh, T. & Novella, R. & Vijayagopal, R., 2024. "A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data," Applied Energy, Elsevier, vol. 358(C).
    2. Gao, Qingchen & Bao, Zhiming & Li, Weizhuo & Gong, Zhichao & Fan, Linhao & Jiao, Kui, 2024. "Performance analysis and gradient-porosity electrode design of vanadium redox flow batteries based on CFD simulations under open-source environment," Energy, Elsevier, vol. 289(C).

    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. Hu, Haowen & Ou, Kai & Yuan, Wei-Wei, 2023. "Fused multi-model predictive control with adaptive compensation for proton exchange membrane fuel cell air supply system," Energy, Elsevier, vol. 284(C).
    2. Deng, Zhihua & Chan, Siew Hwa & Chen, Qihong & Liu, Hao & Zhang, Liyan & Zhou, Keliang & Tong, Sirui & Fu, Zhichao, 2023. "Efficient degradation prediction of PEMFCs using ELM-AE based on fuzzy extension broad learning system," Applied Energy, Elsevier, vol. 331(C).
    3. Quan, Shengwei & Wang, Ya-Xiong & Xiao, Xuelian & He, Hongwen & Sun, Fengchun, 2021. "Feedback linearization-based MIMO model predictive control with defined pseudo-reference for hydrogen regulation of automotive fuel cells," Applied Energy, Elsevier, vol. 293(C).
    4. Liu, Ze & Zhang, Baitao & Xu, Sichuan, 2022. "Research on air mass flow-pressure combined control and dynamic performance of fuel cell system for vehicles application," Applied Energy, Elsevier, vol. 309(C).
    5. Lopez-Juarez, M. & Rockstroh, T. & Novella, R. & Vijayagopal, R., 2024. "A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data," Applied Energy, Elsevier, vol. 358(C).
    6. Lu, Guolong & Liu, Mingxin & Su, Xunkang & Zheng, Tongxi & Luan, Yang & Fan, Wenxuan & Cui, Hao & Liu, Zhenning, 2024. "Study on counter-flow mass transfer characteristics and performance optimization of commercial large-scale proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 359(C).
    7. Zeng, Tao & Xiao, Long & Chen, Jinrui & Li, Yu & Yang, Yi & Huang, Shulong & Deng, Chenghao & Zhang, Caizhi, 2023. "Feedforward-based decoupling control of air supply for vehicular fuel cell system: Methodology and experimental validation," Applied Energy, Elsevier, vol. 335(C).
    8. Pang, Ran & Zhang, Caizhi & Dai, Haifeng & Bai, Yunfeng & Hao, Dong & Chen, Jinrui & Zhang, Bin, 2022. "Intelligent health states recognition of fuel cell by cell voltage consistency under typical operating parameters," Applied Energy, Elsevier, vol. 305(C).
    9. Huang, Ying & Song, Jiangnan & Deng, Xinyue & Chen, Su & Zhang, Xiang & Ma, Zongpeng & Chen, Lunjun & Wu, Yanli, 2023. "Numerical investigation of baffle shape effects on performance and mass transfer of proton exchange membrane fuel cell," Energy, Elsevier, vol. 266(C).
    10. 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).
    11. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    12. Jia, Fei & Tian, Xiaodi & Liu, Fengfeng & Ye, Junjie & Yang, Chengpeng, 2023. "Oxidant starvation under various operating conditions on local and transient performance of proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 331(C).
    13. Aihua Tang & Yuanhang Yang & Quanqing Yu & Zhigang Zhang & Lin Yang, 2022. "A Review of Life Prediction Methods for PEMFCs in Electric Vehicles," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    14. Chen, Dongfang & Wu, Wenlong & Chang, Kuanyu & Li, Yuehua & Pei, Pucheng & Xu, Xiaoming, 2023. "Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization," Energy, Elsevier, vol. 285(C).
    15. Zhang, Chu & Hu, Haowen & Ji, Jie & Liu, Kang & Xia, Xin & Nazir, Muhammad Shahzad & Peng, Tian, 2023. "An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC," Applied Energy, Elsevier, vol. 330(PA).
    16. Zhou, Yu & Chen, Ben, 2023. "Investigation of optimization and evaluation criteria for flow field in proton exchange membrane fuel cell: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    17. Huu-Linh Nguyen & Sang-Min Lee & Sangseok Yu, 2023. "A Comprehensive Review of Degradation Prediction Methods for an Automotive Proton Exchange Membrane Fuel Cell," Energies, MDPI, vol. 16(12), pages 1-32, June.
    18. Fu, Hao & Shen, Jiong & Sun, Li & Lee, Kwang Y., 2021. "In-depth characteristic analysis and wide range optimal operation of fuel cell using multi-model predictive control," Energy, Elsevier, vol. 234(C).
    19. Zhang, Yong & He, Shirong & Jiang, Xiaohui & Xiong, Mu & Ye, Yuntao & Yang, Xi, 2023. "Three-dimensional multi-phase simulation of proton exchange membrane fuel cell performance considering constriction straight channel," Energy, Elsevier, vol. 267(C).
    20. Sun, Li & Sun, Wen & You, Fengqi, 2020. "Core temperature modelling and monitoring of lithium-ion battery in the presence of sensor bias," Applied Energy, Elsevier, vol. 271(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:appene:v:325:y:2022:i:c:s0306261922011084. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.