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Dynamic performance of the transcritical power cycle using CO2-based binary zeotropic mixtures for truck engine waste heat recovery

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  • Shu, Gequn
  • Wang, Rui
  • Tian, Hua
  • Wang, Xuan
  • Li, Xiaoya
  • Cai, Jinwen
  • Xu, Zhiqiang

Abstract

CO2 transcritical power cycle (CTPC) technology has received substantial interest and attention for use in waste heat recovery, but its high operating pressure and low condensing temperature restrict its wide application. CO2-based binary zeotropic mixtures are considered a promising solution. Therefore, a CTPC system dynamic model with different CO2 mixtures as the working fluids in the context of engine waste heat recovery is examined using Simulink simulation to understand the effects of different mixtures and composition ratios on system performance in various working conditions. A system dynamic model of the system is thoroughly validated against experimental data, and the results are reasonably consistent. Based on these foundations, the dynamic response of the CTPC system with CO2 mixtures of different proportions and components is compared and analysed. The results show that the system responds faster when the proportion of CO2 is greater. The proportion of refrigerant also affects the optimal net power output and thermal efficiency. The preliminary results presented in this paper will be helpful for future design of CO2 transcritical power cycles and the development of control strategies for these systems.

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  • Shu, Gequn & Wang, Rui & Tian, Hua & Wang, Xuan & Li, Xiaoya & Cai, Jinwen & Xu, Zhiqiang, 2020. "Dynamic performance of the transcritical power cycle using CO2-based binary zeotropic mixtures for truck engine waste heat recovery," Energy, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:energy:v:194:y:2020:i:c:s0360544219325204
    DOI: 10.1016/j.energy.2019.116825
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    Cited by:

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    2. Yu, Aofang & Xing, Lingli & Su, Wen & Liu, Pei, 2023. "State-of-the-art review on the CO2 combined power and cooling system: System configuration, modeling and performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    3. Bian, Xingyan & Wang, Xuan & Wang, Rui & Cai, Jinwen & Tian, Hua & Shu, Gequn & Lin, Zhimin & Yu, Xiangyu & Shi, Lingfeng, 2022. "A comprehensive evaluation of the effect of different control valves on the dynamic performance of a recompression supercritical CO2 Brayton cycle," Energy, Elsevier, vol. 248(C).
    4. He, Jintao & Zhang, Yonghao & Tian, Hua & Wang, Xuan & Li, Ligeng & Cai, Jinwen & Shi, Lingfeng & Shu, Gequn, 2022. "Dynamic performance of a multi-mode operation CO2-based system combining cooling and power generation," Applied Energy, Elsevier, vol. 312(C).
    5. Lu, Bowen & Zhang, Zhifu & Cai, Jinwen & Wang, Wei & Ju, Xueming & Xu, Yao & Lu, Xun & Tian, Hua & Shi, Lingfeng & Shu, Gequn, 2023. "Integrating engine thermal management into waste heat recovery under steady-state design and dynamic off-design conditions," Energy, Elsevier, vol. 272(C).
    6. Xingyan, Bian & Wang, Xuan & Wang, Rui & Cai, Jinwen & Tian, Hua & Shu, Gequn, 2022. "Optimal selection of supercritical CO2 Brayton cycle layouts based on part-load performance," Energy, Elsevier, vol. 256(C).
    7. Cai, Jinwen & Tian, Hua & Wang, Xuan & Wang, Rui & Shu, Gequn & Wang, Mingtao, 2021. "A calibrated organic Rankine cycle dynamic model applying to subcritical system and transcritical system," Energy, Elsevier, vol. 237(C).

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