Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v297y2024ics0360544224010521.html
   My bibliography  Save this article

Optimization of thermal management system architecture in hydrogen engine employing improved genetic algorithm

Author

Listed:
  • Wen, Jie
  • Wan, Chenxi
  • Xu, Guoqiang
  • Zhuang, Laihe
  • Dong, Bensi
  • Chen, Junjie
Abstract
Decarbonization in the aeronautical industry is a daunting challenge due to the lack of sustainable aviation fuel. Hydrogen offers a potential option for this problem, given that it is an energy-dense fuel capable of reducing climate impact. Along with it, the liquid hydrogen preheating and thermal protection bring inevitable safety issues. Currently, how to construct the optimal thermal management system (TMS) architecture and further clarify its principles is still unclear. Thus, this study compares different TMS architectures through optimized genetic algorithms (GA), and firstly points out the excellent architecture as well as its operating parameters. Strikingly, our results reveal the optimized algorithm can significantly improve efficiency and precision of the optimizing processes. Benefiting from adaptive population strategy and elite preservation strategy, optimized GA saves half the time compared to conventional GA, and the variance is 60 % smaller than that of conventional GA. Using optimized GA, the series-parallel scheme is determined as the best solution and it exhibits better advantages on lightweight. In addition, results also show the leading factor is air/helium heat exchanger area. In conclusion, we hope this work can provide guidance for the optimal GA, contribute to decarbonization, and provide more ideas for the optimization of hydrogen TMS in the future.

Suggested Citation

  • Wen, Jie & Wan, Chenxi & Xu, Guoqiang & Zhuang, Laihe & Dong, Bensi & Chen, Junjie, 2024. "Optimization of thermal management system architecture in hydrogen engine employing improved genetic algorithm," Energy, Elsevier, vol. 297(C).
    • Handle: RePEc:eee:energy:v:297:y:2024:i:c:s0360544224010521
    DOI: 10.1016/j.energy.2024.131279
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224010521
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.131279?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. Aydın, Emre & Turan, Onder, 2023. "Performance models of passenger aircraft and propulsion systems based on particle swarm and Spotted Hyena Optimization methods," Energy, Elsevier, vol. 268(C).
    2. Cai, Changpeng & Chen, Haoying & Fang, Juan & Zheng, Qiangang & Chen, Cheng & Zhang, Haibo, 2023. "Thermodynamic analysis of a novel precooled supersonic turbine engine based on aircraft/engine integrated optimal design," Energy, Elsevier, vol. 280(C).
    3. Burston, Martin & Ranasinghe, Kavindu & Gardi, Alessandro & Parezanović, Vladimir & Ajaj, Rafic & Sabatini, Roberto, 2022. "Design principles and digital control of advanced distributed propulsion systems," Energy, Elsevier, vol. 241(C).
    4. Woon, Kok Sin & Phuang, Zhen Xin & Taler, Jan & Varbanov, Petar Sabev & Chong, Cheng Tung & Klemeš, Jiří Jaromír & Lee, Chew Tin, 2023. "Recent advances in urban green energy development towards carbon emissions neutrality," Energy, Elsevier, vol. 267(C).
    5. Zhang, Duo & Chen, Chen & Yu, Xuanfei, 2023. "Control law synthetizing for an innovative indirect precooled airbreathing engine under off-design operation conditions," Energy, Elsevier, vol. 263(PE).
    6. Baklacioglu, Tolga & Turan, Onder & Aydin, Hakan, 2015. "Dynamic modeling of exergy efficiency of turboprop engine components using hybrid genetic algorithm-artificial neural networks," Energy, Elsevier, vol. 86(C), pages 709-721.
    7. Aygun, Hakan & Cilgin, Mehmet Emin & Ekmekci, Ismail & Turan, Onder, 2020. "Energy and performance optimization of an adaptive cycle engine for next generation combat aircraft," Energy, Elsevier, vol. 209(C).
    8. Aygun, Hakan & Kirmizi, Mehmet & Kilic, Ulas & Turan, Onder, 2023. "Multi-objective optimization of a small turbojet engine energetic performance," Energy, Elsevier, vol. 271(C).
    9. Aygun, Hakan & Turan, Onder, 2022. "Application of genetic algorithm in exergy and sustainability: A case of aero-gas turbine engine at cruise phase," Energy, Elsevier, vol. 238(PA).
    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. Lv, Chengkun & Huang, Qian & Wang, Ziao & Chang, Juntao & Yu, Daren, 2024. "Mode transition control law analysis of ammonia MIPCC aeroengine considering inlet–compressor safety matching," Energy, Elsevier, vol. 288(C).
    2. Wang, Busheng & Xuan, Yimin, 2024. "Heuristic deepening of aero engine performance analysis model based on thermodynamic principle of variable mass system," Energy, Elsevier, vol. 306(C).
    3. Kagan Ayaz, S. & Caliskan, Hakan & Altuntas, Onder, 2023. "Environmental and second law analysis of a turbojet engine operating with different fuels," Energy, Elsevier, vol. 285(C).
    4. Balli, Ozgur & Karakoc, T. Hikmet, 2022. "Exergetic, exergoeconomic, exergoenvironmental damage cost and impact analyses of an aircraft turbofan engine(ATFE)," Energy, Elsevier, vol. 256(C).
    5. Cai, Changpeng & Zheng, Qiangang & Wang, Yong & Chen, Haoying & Zhang, Haibo, 2024. "Predictive control method for mode transition process of multi-mode turbine engine based on onboard adaptive composite model," Energy, Elsevier, vol. 302(C).
    6. Shenhua Liu & Deheng Xiao, 2024. "Can Big Data Comprehensive Pilot Zone Promote Low-Carbon Urban Development? Evidence from China," Sustainability, MDPI, vol. 17(1), pages 1-15, December.
    7. Aygun, Hakan & Cilgin, Mehmet Emin & Ekmekci, Ismail & Turan, Onder, 2020. "Energy and performance optimization of an adaptive cycle engine for next generation combat aircraft," Energy, Elsevier, vol. 209(C).
    8. Wang, Busheng & Xuan, Yimin, 2023. "An integrated model for energy management of aero engines based on thermodynamic principle of variable mass systems," Energy, Elsevier, vol. 276(C).
    9. Aygun, Hakan, 2022. "Thermodynamic, environmental and sustainability calculations of a conceptual turboshaft engine under several power settings," Energy, Elsevier, vol. 245(C).
    10. Chountalas, Theofanis D. & Founti, Maria & Tsalavoutas, Ioannis, 2023. "Evaluation of biofuel effect on performance & emissions of a 2-stroke marine diesel engine using on-board measurements," Energy, Elsevier, vol. 278(C).
    11. Aygun, Hakan & Kirmizi, Mehmet & Turan, Onder, 2022. "Propeller effects on energy, exergy and sustainability parameters of a small turboprop engine," Energy, Elsevier, vol. 249(C).
    12. Zha, Xiaojian & Zhang, Zewu & Zhao, Zhenghong & Yang, Long & Mao, Wenchao & Wu, Fan & Li, Xiaoshan & Luo, Cong & Zhang, Liqi, 2024. "Comparative study on co-firing characteristics of normal and superfine pulverized coal blended with NH3 under the MILD combustion mode," Energy, Elsevier, vol. 305(C).
    13. Chin, Min Yee & Qin, Yuting & Hoy, Zheng Xuan & Farooque, Aitazaz Ahsan & Wong, Keng Yinn & Mong, Guo Ren & Tan, Jian Ping & Woon, Kok Sin, 2024. "Assessing carbon budgets and reduction pathways in different income levels with neural network forecasting," Energy, Elsevier, vol. 305(C).
    14. Wang, Shuofeng & Sun, Yu & Yang, Jinxin & Wang, Huaiyu, 2024. "Effect of excess air ratio and ignition timing on the combustion and emission characteristics of the ammonia-hydrogen Wankel rotary engine," Energy, Elsevier, vol. 302(C).
    15. Zheng, Qiangang & Zhang, Hongwei & Hu, Chenxu & Zhang, Haibo, 2024. "Performance seeking control method for minimum pollutant emission mode for turbofan engine," Energy, Elsevier, vol. 289(C).
    16. Nezamoddini, Nasim & Gholami, Amirhosein & Aqlan, Faisal, 2020. "A risk-based optimization framework for integrated supply chains using genetic algorithm and artificial neural networks," International Journal of Production Economics, Elsevier, vol. 225(C).
    17. Cao, Li-hua & Yu, Jing-wen & Li, Yong, 2016. "Study on the determination method of the normal value of relative internal efficiency of the last stage group of steam turbine," Energy, Elsevier, vol. 98(C), pages 101-107.
    18. Jie Gao & Qingmei Tan & Bo Cui, 2024. "Evolutionary Game Analysis of New Energy Transition Among Government, Traditional Automobile Enterprises, and Research Institutions Under the Dual Carbon Goals," Energies, MDPI, vol. 17(23), pages 1-20, November.
    19. Rozhkov, Anton, 2024. "Applying graph theory to find key leverage points in the transition toward urban renewable energy systems," Applied Energy, Elsevier, vol. 361(C).
    20. Aygun, Hakan & Erkara, Seref & Turan, Onder, 2022. "Comprehensive exergo- sustainability analysis for a next generation aero engine," Energy, Elsevier, vol. 239(PD).

    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:297:y:2024:i:c:s0360544224010521. 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.