IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v317y2025ics0360544225002142.html
   My bibliography  Save this article

Waste heat recycling from phosphoric acid fuel cells for desalination with hydrophilic modified tubular stills: Performance prediction and regulation

Author

Listed:
  • Li, Hao
  • Zhou, Xingfei
  • Hu, Ziyang
  • Zhang, Houcheng

Abstract

Phosphoric acid fuel cells are a promising technology for clean energy generation; however, a significant portion of the fuel's chemical energy is transformed into waste heat, reducing overall efficiency and potentially affecting long-term durability. This study aims to address these limitations by integrating a hydrophilic modified tubular still to recycle waste heat for seawater desalination, forming a novel hybrid system capable of simultaneous electricity generation and freshwater production. To evaluate the effectiveness, the vital evaluation metrics for the hybrid system are analytically derived through the establishment of a mathematical framework. The hybrid system achieves significant improvements over a standalone system, with enhancements reaching up to 22.86 % in power density, 12.18 % in exergetic efficiency, and 12.63 % in energetic efficiency. A comprehensive parametric analysis reveals that increasing the exchange current density, operation temperature, environment temperature, and charge transfer coefficient, while reducing phosphoric acid concentration, tubular shell diameter, wind velocity, and electrolyte thickness, positively impact the hybrid system's performance. Local sensitivity analysis pinpoints electrolyte thickness as the most sensitive parameter affecting performance, while environment temperature has the least sensitivity. These results offer insightful guidance for designing and running such a high-performance hybrid system, with the potential to enhance both efficiency and operational longevity.

Suggested Citation

  • Li, Hao & Zhou, Xingfei & Hu, Ziyang & Zhang, Houcheng, 2025. "Waste heat recycling from phosphoric acid fuel cells for desalination with hydrophilic modified tubular stills: Performance prediction and regulation," Energy, Elsevier, vol. 317(C).
  • Handle: RePEc:eee:energy:v:317:y:2025:i:c:s0360544225002142
    DOI: 10.1016/j.energy.2025.134572
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225002142
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.134572?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Wei & Xu, Chenbin & Wu, Haibo & Bai, Yang & Li, Zoulu & Zhang, Bin, 2020. "Energy and exergy analyses of a novel hybrid system consisting of a phosphoric acid fuel cell and a triple-effect compression–absorption refrigerator with [mmim]DMP/CH3OH as working fluid," Energy, Elsevier, vol. 195(C).
    2. Baz, Khan & Cheng, Jinhua & Xu, Deyi & Abbas, Khizar & Ali, Imad & Ali, Hashmat & Fang, Chuandi, 2021. "Asymmetric impact of fossil fuel and renewable energy consumption on economic growth: A nonlinear technique," Energy, Elsevier, vol. 226(C).
    3. Wu, Zhen & Zhu, Pengfei & Yao, Jing & Tan, Peng & Xu, Haoran & Chen, Bin & Yang, Fusheng & Zhang, Zaoxiao & Ni, Meng, 2020. "Thermo-economic modeling and analysis of an NG-fueled SOFC-WGS-TSA-PEMFC hybrid energy conversion system for stationary electricity power generation," Energy, Elsevier, vol. 192(C).
    4. Ghouse, M. & Abaoud, H. & Al-Boeiz, A. & AbdulHadi, M., 1998. "Development of a 1 kW Phosphoric Acid Fuel Cell stack," Applied Energy, Elsevier, vol. 60(3), pages 153-167, July.
    5. Wilailak, Supaporn & Yang, Jae-Hyeon & Heo, Chul-Gu & Kim, Kyung-Su & Bang, Se-Kyung & Seo, In-Ho & Zahid, Umer & Lee, Chul-Jin, 2021. "Thermo-economic analysis of Phosphoric Acid Fuel-Cell (PAFC) integrated with Organic Ranking Cycle (ORC)," Energy, Elsevier, vol. 220(C).
    6. Huang, Ruchen & He, Hongwen & Su, Qicong, 2024. "Towards a fossil-free urban transport system: An intelligent cross-type transferable energy management framework based on deep transfer reinforcement learning," Applied Energy, Elsevier, vol. 363(C).
    7. Chen, Xiaohang & Wang, Yuan & Zhao, Yingru & Zhou, Yinghui, 2016. "A study of double functions and load matching of a phosphoric acid fuel cell/heat-driven refrigerator hybrid system," Energy, Elsevier, vol. 101(C), pages 359-365.
    8. Manju, S. & Sagar, Netramani, 2017. "Renewable energy integrated desalination: A sustainable solution to overcome future fresh-water scarcity in India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 594-609.
    9. Yeo, Lip Siang & Teng, Sin Yong & Ng, Wendy Pei Qin & Lim, Chun Hsion & Leong, Wei Dong & Lam, Hon Loong & Wong, Yat Choy & Sunarso, Jaka & How, Bing Shen, 2022. "Sequential optimization of process and supply chains considering re-refineries for oil and gas circularity," Applied Energy, Elsevier, vol. 322(C).
    10. Wang, Yifei & Luo, Shijing & Kwok, Holly Y.H. & Pan, Wending & Zhang, Yingguang & Zhao, Xiaolong & Leung, Dennis Y.C., 2021. "Microfluidic fuel cells with different types of fuels: A prospective review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    11. Xie, Guo & Sun, Licheng & Yan, Tiantong & Tang, Jiguo & Bao, Jingjing & Du, Min, 2018. "Model development and experimental verification for tubular solar still operating under vacuum condition," Energy, Elsevier, vol. 157(C), pages 115-130.
    12. Guo, Xinru & Zhang, Houcheng & Hu, Ziyang & Hou, Shujin & Ni, Meng & Liao, Tianjun, 2021. "Energetic, exergetic and ecological evaluations of a hybrid system based on a phosphoric acid fuel cell and an organic Rankine cycle," Energy, Elsevier, vol. 217(C).
    13. Huang, Ruchen & He, Hongwen & Gao, Miaojue, 2023. "Training-efficient and cost-optimal energy management for fuel cell hybrid electric bus based on a novel distributed deep reinforcement learning framework," Applied Energy, Elsevier, vol. 346(C).
    14. Wu, Shuang-Ying & Yuan, Xiao-Feng & Li, You-Rong & Xiao, Lan, 2007. "Exergy transfer effectiveness on heat exchanger for finite pressure drop," Energy, Elsevier, vol. 32(11), pages 2110-2120.
    15. Huang, Ruchen & He, Hongwen & Zhao, Xuyang & Wang, Yunlong & Li, Menglin, 2022. "Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm," Applied Energy, Elsevier, vol. 321(C).
    Full references (including those not matched with items on IDEAS)

    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. Kim, Hyerim & Kim, Tong Seop, 2024. "Optimal design and dispatch of phosphoric acid fuel cell hybrid system with direct heat recovery through coupled calculation and artificial intelligence-based optimization," Energy, Elsevier, vol. 312(C).
    2. Zhu, Huichao & Zhang, Houcheng, 2023. "Upgrading the low-grade waste heat from alkaline fuel cells via isopropanol-acetone-hydrogen chemical heat pumps," Energy, Elsevier, vol. 265(C).
    3. Huang, Ruchen & He, Hongwen & Su, Qicong, 2024. "Smart energy management for hybrid electric bus via improved soft actor-critic algorithm in a heuristic learning framework," Energy, Elsevier, vol. 309(C).
    4. Niu, Zegong & He, Hongwen, 2024. "A data-driven solution for intelligent power allocation of connected hybrid electric vehicles inspired by offline deep reinforcement learning in V2X scenario," Applied Energy, Elsevier, vol. 372(C).
    5. Zhang, Houcheng & Li, Jiarui & Xue, Yejian & Grgur, Branimir N. & Li, Jianming, 2024. "Performance prediction and regulation of a tubular solid oxide fuel cell and hydrophilic modified tubular still hybrid system for electricity and freshwater cogeneration," Energy, Elsevier, vol. 289(C).
    6. Huang, Ruchen & He, Hongwen & Su, Qicong & Härtl, Martin & Jaensch, Malte, 2024. "Enabling cross-type full-knowledge transferable energy management for hybrid electric vehicles via deep transfer reinforcement learning," Energy, Elsevier, vol. 305(C).
    7. Tang, Tianfeng & Peng, Qianlong & Shi, Qing & Peng, Qingguo & Zhao, Jin & Chen, Chaoyi & Wang, Guangwei, 2024. "Energy management of fuel cell hybrid electric bus in mountainous regions: A deep reinforcement learning approach considering terrain characteristics," Energy, Elsevier, vol. 311(C).
    8. Park, Heejin & Jung, Yoonju & Park, Chungi & Lee, Jaeseung & Ghasemi, Masoomeh & Alam, Afroz & Kim, Hyeonjin & Kim, Jinwook & Park, Sojin & Choi, Kyungshik & You, Hyunseok & Ju, Hyunchul, 2023. "Performance evaluation and economic feasibility of a PAFC-based multi-energy hub system in South Korea," Energy, Elsevier, vol. 278(PB).
    9. Li, Jie & Li, Jianming & Xiao, Liusheng & Zhao, Jiapei & Kuang, Min & Zhang, Houcheng, 2024. "Performance prediction and enhancement strategy of a new proton exchange membrane fuel cell-hydrophilic modified tubular still hybrid system," Renewable Energy, Elsevier, vol. 237(PC).
    10. Chen, Wei & Xu, Chenbin & Wu, Haibo & Bai, Yang & Li, Zoulu & Zhang, Bin, 2020. "Energy and exergy analyses of a novel hybrid system consisting of a phosphoric acid fuel cell and a triple-effect compression–absorption refrigerator with [mmim]DMP/CH3OH as working fluid," Energy, Elsevier, vol. 195(C).
    11. Wang, Renkang & Li, Kai & Ming, Yuan & Guo, Wenjun & Deng, Bo & Tang, Hao, 2024. "An enhanced salp swarm algorithm with chaotic mapping and dynamic learning for optimizing purge process of proton exchange membrane fuel cell systems," Energy, Elsevier, vol. 308(C).
    12. Rezk, Hegazy & Ferahtia, Seydali & Djeroui, Ali & Chouder, Aissa & Houari, Azeddine & Machmoum, Mohamed & Abdelkareem, Mohammad Ali, 2022. "Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer," Energy, Elsevier, vol. 239(PC).
    13. Dai, Churong & Zuo, Wei & Li, Qingqing & Zhou, Kun & Huang, Yuhan & Zhang, Guangde & E, Jiaqiang, 2024. "Energy conversion efficiency improvement studies on the hydrogen-fueled micro planar combustor with multi-baffles for thermophotovoltaic applications," Energy, Elsevier, vol. 313(C).
    14. Fang, Shuo & Hu, Shuangxi & Liu, Yuntao & Zhao, Chunhui & Wang, Ying, 2025. "Power management unit with maximum-efficiency-point-tracking to enhance the efficiency of micro DMFC stack," Energy, Elsevier, vol. 315(C).
    15. Chen, Wei & Chenbin, Xu & Wu, Haibo & Li, Zoulu & Zhang, Bin & Yan, He, 2021. "Thermal analysis and optimization of combined cold and power system with integrated phosphoric acid fuel cell and two-stage compression–absorption refrigerator at low evaporation temperature," Energy, Elsevier, vol. 216(C).
    16. Huang, Ruchen & He, Hongwen & Su, Qicong & Härtl, Martin & Jaensch, Malte, 2025. "Type- and task-crossing energy management for fuel cell vehicles with longevity consideration: A heterogeneous deep transfer reinforcement learning framework," Applied Energy, Elsevier, vol. 377(PC).
    17. Huang, Ruchen & He, Hongwen & Su, Qicong, 2024. "An intelligent full-knowledge transferable collaborative eco-driving framework based on improved soft actor-critic algorithm," Applied Energy, Elsevier, vol. 375(C).
    18. He, Hongwen & Su, Qicong & Huang, Ruchen & Niu, Zegong, 2024. "Enabling intelligent transferable energy management of series hybrid electric tracked vehicle across motion dimensions via soft actor-critic algorithm," Energy, Elsevier, vol. 294(C).
    19. Karmegam Dhanabalan & Muthukumar Perumalsamy & Ganesan Sriram & Nagaraj Murugan & Shalu & Thangarasu Sadhasivam & Tae Hwan Oh, 2023. "Metal–Organic Framework (MOF)-Derived Catalyst for Oxygen Reduction Reaction (ORR) Applications in Fuel Cell Systems: A Review of Current Advancements and Perspectives," Energies, MDPI, vol. 16(13), pages 1-19, June.
    20. Gritli, Mohamed Ilyes & Charfi, Fatma Marrakchi, 2023. "The determinants of oil consumption in Tunisia: Fresh evidence from NARDL approach and asymmetric causality test," Energy, Elsevier, vol. 284(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:317:y:2025:i:c:s0360544225002142. 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.journals.elsevier.com/energy .

    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.