Surrogate Prediction of Transient Discharging Performance of a Fin-and-Tube Phase Change Cold Storage Unit

Han Han; Chen Liang; Li Yunkai; Chen Shuangtao Hou Yu

doi:10.12465/issn.0253-4339.20260424001

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Surrogate Prediction of Transient Discharging Performance of a Fin-and-Tube Phase Change Cold Storage Unit

更新时间：2026-06-29

- Surrogate Prediction of Transient Discharging Performance of a Fin-and-Tube Phase Change Cold Storage Unit
- Journal of Refrigeration Pages: 1-10(2026)
- 作者机构：
  
  1.西安交通大学能源与动力工程学院西安 710049
  2. 高能高功率脉冲电源全国重点实验室（西安交通大学）西安 710049
- 作者简介：
  
  Chen Liang， male， professor， School of Energy and Power Engineering， Xi'an Jiaotong University， 86-17802932445， E-mail： liangchen@xjtu.edu.cn. Research fields： lightweight and miniaturized technologies for thermal control and refrigeration systems， and optimization of high-temperature and high-pressure microchannel heat exchangers.
- 基金信息：
  
  the National Natural Science Foundation of China(52176020)
- DOI：10.12465/issn.0253-4339.20260424001
  CLC： TB61⁺1;TK11;TP181
- Received：24 April 2026，
  
  Revised：2026-05-14，
  
  Accepted：23 May 2026，
  
  Online First：29 June 2026，
- 稿件说明：
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韩瀚，陈良，李云凯，等. 管翅式相变蓄冷器瞬态释冷代理预测［J］. 制冷学报，XXXX，XX（XX）：1-10.

Han Han，Chen Liang，Li Yunkai，et al. Surrogate Prediction of Transient Discharging Performance of a Fin-and-Tube Phase Change Cold Storage Unit［J］. Journal of Refrigeration，XXXX，XX（XX）：1-10.
韩瀚，陈良，李云凯，等. 管翅式相变蓄冷器瞬态释冷代理预测［J］. 制冷学报，XXXX，XX（XX）：1-10. DOI： 10.12465/issn.0253-4339.20260424001.

Han Han，Chen Liang，Li Yunkai，et al. Surrogate Prediction of Transient Discharging Performance of a Fin-and-Tube Phase Change Cold Storage Unit［J］. Journal of Refrigeration，XXXX，XX（XX）：1-10. DOI： 10.12465/issn.0253-4339.20260424001.

摘要

面向短时高热负荷热管理系统轻量化与实时控制需求，针对传统数值模拟难以兼顾机理解析与在线预测效率的问题，本文开展了管翅式相变蓄冷器瞬态释冷性能预测研究。构建了基于焓-孔隙率法的管外相变材料三维非稳态模型与管内制冷剂一维瞬态流动模型，并建立三维-一维双向热耦合求解框架，以揭示蓄冷器内相变传热与沿程压降耦合作用下的瞬态响应规律。结果表明：在典型工况下，蓄冷器80 s工作周期内平均传热功率为88.29 kW；随着相变过程推进，液相层增厚导致传热热阻增大，装置传热能力持续衰减；80 s时管内沿程压降接近0.3 MPa，高压降诱导的饱和温度下降是出口温度出现非单调拐点的主要原因。为实现快速性能预测，进一步构建了经粒子群算法优化并嵌入输运延迟判据与热力学一致性约束的极端梯度提升代理模型。预测结果表明，该模型在独立测试集上对出口压力、出口焓值、相变材料平均温度的决定系数均高于0.98，物理输运延迟判据可使制冷剂出口温度预测的均方根误差从1.214 ℃降至0.580 ℃。该方法可为相变蓄冷系统快速性能评估与系统级模型预测控制提供技术支撑。

Abstract

To meet the demands of lightweight design and real-time control in short-duration， high-heat-load thermal management systems， this study investigated the transient discharge performance of a fin-and-tube phase-change cold storage unit to address the limitations of conventional numerical simulations in simultaneously providing physical insight and online prediction efficiency. First， a three-dimensional transient model for the external phase change material based on the enthalpy-porosity method and a one-dimensional transient flow model for the internal refrigerant were established. A coupled three-dimensional/one-dimensional bidirectional thermal framework was developed to reveal the transient response of the cold storage unit under the combined effects of phase-change heat transfer and along-tube pressure drop. The results show that， under typical operating conditions， the average heat transfer rate reaches 88.29 kW over an 80 s operating period. As the phase change proceeds， the thickened liquid layer increases thermal resistance and continuously weakens the heat transfer capacity of the unit. At 80 s， the along-tube pressure drop approaches 0.3 MPa， and the pressure-drop-induced decrease in saturation temperature is identified as the primary cause of the non-monotonic inflection in the outlet temperature. To enable rapid performance prediction， a particle swarm optimization Extreme Gradient Boosting surrogate model embedded with a transport delay criterion and thermodynamic consistency constraints was developed. The prediction results show that the coefficients of determination for the outlet pressure， outlet enthalpy， and average phase change material temperature of the independent test set exceed 0.98. Crucially， the transport delay criterion reduces the root mean square error of the refrigerant outlet temperature prediction from 1.214 ℃ to 0.580 ℃， providing technical support for the rapid performance evaluation of phase-change cold storage systems and system-level model predictive control.

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