电池直冷热管理系统的动态建模及模型预测控制研究

王家锋; 徐象国

doi:10.12465/j.issn.0253-4339.2025.06.023

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电池直冷热管理系统的动态建模及模型预测控制研究

更新时间：2025-12-03

- 电池直冷热管理系统的动态建模及模型预测控制研究
- Dynamic Modeling and Model Predictive Control Study of Direct Cooling Thermal Management System for Batteries
- 制冷学报 2025年46卷第6期页码：23-33
- 作者机构：
  
  1.浙江大学宁波科创中心　宁波　 315100
  2.浙江大学制冷与低温研究所浙江省制冷与低温技术重点实验室　杭州　 310027
  3.浙江大学平衡建筑研究中心　杭州　 310027
- 作者简介：
  
  徐象国，男，教授，浙江大学制冷与低温研究所，0571-87953944，E-mail：zjuxgxu@zju.edu.cn。研究方向：空调系统模拟、动态特性以及高级控制算法开发，新能源汽车热管理技术。
- 基金信息：
  
  国家自然科学基金(51976181);中央高校基本科研业务费专项资金(2022FZZX01-09)
- DOI：10.12465/j.issn.0253-4339.2025.06.023
  中图分类号： TB61⁺1;TP273;TM912
- 收稿：2024-11-25，
  
  修回：2025-02-14，
  
  录用：2025-02-19，
  
  纸质出版：2025-12-16
- 稿件说明：
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王家锋, 徐象国. 电池直冷热管理系统的动态建模及模型预测控制研究[J]. 制冷学报, 2025,46(6):23-33.

Wang Jiafeng, Xu Xiangguo. Dynamic Modeling and Model Predictive Control Study of Direct Cooling Thermal Management System for Batteries[J]. Journal of Refrigeration, 2025, 46(6): 23-33.
王家锋, 徐象国. 电池直冷热管理系统的动态建模及模型预测控制研究[J]. 制冷学报, 2025,46(6):23-33. DOI： 10.12465/j.issn.0253-4339.2025.06.023.

Wang Jiafeng, Xu Xiangguo. Dynamic Modeling and Model Predictive Control Study of Direct Cooling Thermal Management System for Batteries[J]. Journal of Refrigeration, 2025, 46(6): 23-33. DOI： 10.12465/j.issn.0253-4339.2025.06.023.

摘要

基于制冷剂直接冷却的电池热管理系统具有多干扰、强耦合及非线性特征，传统PID控制在电池温度调节过程存在超调现象且难以兼顾节能需求。基于第一性原理建立了直冷热管理系统的动态降阶模型，并利用实验数据验证了其线性化模型。基于该模型设计了一种线性时变模型预测控制（MPC）策略，并在电池冷却和WLTC驾驶循环2种工况下与PID控制进行对比。结果表明：在电池发热量恒定条件下，对比电池温度由50 ℃降至30 ℃的稳定时间，MPC控制策略为262 s，PID控制策略为965 s，同时MPC节约2.47%的能耗。在WLTC工况中，PID控制的温度波动较大，最大偏差为2.9 ℃，而MPC能够快速响应热负荷变化，稳定控制温度在30 ℃。2种控制策略的温度变化标准差分别为1.21 ℃和0.044 ℃，MPC策略在温度调节速度、能效及鲁棒性方面均优于PID控制。

Abstract

Battery thermal-management systems based on direct refrigerant cooling are characterized by multiple sources of disturbance

strong coupling

and nonlinearity

making regulation of the temperature difficult through traditional proportional-integral-derivative (PID) controllers. In this study

a dynamic step-down model of a direct cooling thermal-management system was first established based on the first principle

and its linearized model was verified using experimental data. Based on this model

a linear time-varying model-based predictive control strategy was designed and compared with PID control under two operating conditions: battery cooling and the worldwide harmonized light vehicles test cycle (WLTC). Under the condition of constant battery heat generation

the stabilization time for the battery temperature from 50 ℃ to 30 ℃ was 262 s for the model predictive control (MPC) strategy and 952 s for the PID control strategy. At the same time

the MPC reduced the energy consumption by 5.57%. Under the WLTC condition

the temperature fluctuation of the PID control was large

with a maximum deviation of 2.9 ℃

while the MPC was able to respond quickly to a heat load change and stabilize the control temperature at 30 ℃. The standard temperature deviations of the PID and MPC control strategies were 1.7 ℃ and 0.06 ℃

respectively. In summary

the MPC strategy was superior to the PID control in terms of temperature regulation speed

energy efficiency

and robustness.

关键词

Keywords

references

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