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A novel multi-objective optimization scheme of electric turbo compressor system in hydrogen fuel cell for reducing energy consumption and axial thrust

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  • Wang, Zhen
  • Zhao, Rongchao
  • Zhu, Zhiyong
  • Zhuge, Weilin
  • Zhang, Yangjun

Abstract

Electric turbo compressor (ETC) can recover the exhaust energy and reduce the motor power consumption, which is the future development of the air management system for fuel cell. However, the large imbalances of axial thrust and energy between the compressor and turbine leads to low reliability and efficiency of ETC. In this study, a multi-objective optimization scheme was proposed to explore the lowest ETC axial thrust and electric power consumption. First, the coupled model including compressor, turbine and axial thrust sub-models were established in MATLAB. To verify the model, computational fluid dynamics(CFD) model were established in ANSYS CFX and experimental tests were carried out. The electric power differences between the MATLAB model and experiment is within 4.36 % and the axial thrust deviations between the MATLAB and CFD model is within 5.46 %.Then, eight geometric parameters of compressor and turbine rotors are selected as independent optimization variables. NSGA-ΙΙ multi-objective optimization algorithm was adopted to search for low axial thrust and power consumption solutions. Finally, the optimization results show that the efficiency of the compressor and turbine is increased by 6.39 % and 2.75 % at design point, respectively. The electric power consumed by the motor is reduced by 7.80 % and the axial thrust of the ETC is reduced by 18.83 %.

Suggested Citation

  • Wang, Zhen & Zhao, Rongchao & Zhu, Zhiyong & Zhuge, Weilin & Zhang, Yangjun, 2024. "A novel multi-objective optimization scheme of electric turbo compressor system in hydrogen fuel cell for reducing energy consumption and axial thrust," Energy, Elsevier, vol. 309(C).
    • Handle: RePEc:eee:energy:v:309:y:2024:i:c:s0360544224028718
    DOI: 10.1016/j.energy.2024.133096
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    References listed on IDEAS

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    1. Fu, Jianqin & Wang, Huailin & Sun, Xilei & Bao, Huanhuan & Wang, Xun & Liu, Jingping, 2024. "Multi-objective optimization for impeller structure parameters of fuel cell air compressor using linear-based boosting model and reference vector guided evolutionary algorithm," Applied Energy, Elsevier, vol. 363(C).
    2. Sayadi, Saeed & Tsatsaronis, George & Duelk, Christian, 2014. "Exergoeconomic analysis of vehicular PEM (proton exchange membrane) fuel cell systems with and without expander," Energy, Elsevier, vol. 77(C), pages 608-622.
    3. Sun, Xilei & Fu, Jianqin, 2024. "Many-objective optimization of BEV design parameters based on gradient boosting decision tree models and the NSGA-III algorithm considering the ambient temperature," Energy, Elsevier, vol. 288(C).
    4. Zhao, Rongchao & Huang, Lei & Wang, Zhen & Zhuge, Weilin & Ding, Zhanming & Zhang, Yangjun, 2023. "Development of a novel dual-loop optimization method for the engine electric turbocompound system based on particle swarm algorithm," Energy, Elsevier, vol. 284(C).
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