吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (3): 820-828.doi: 10.13229/j.cnki.jdxbgxb.20230564

• 车辆工程·机械工程 • 上一篇    下一篇

冬季网联纯电动汽车热泵空调生态制热控制方法

宫洵1(),任航1,张华霖2,汪介瑜1,胡云峰3,4,孙耀3()   

  1. 1.吉林大学 人工智能学院，长春 130012
    2.西南大学 工程技术学院，重庆 400715
    3.吉林大学 汽车底盘集成与仿生全国重点实验室，长春 130022
    4.吉林大学 通信工程学院，长春 130012
  • 收稿日期:2023-06-05 出版日期:2025-03-01 发布日期:2025-05-20
  • 通讯作者: 孙耀 E-mail:gongxun@jlu.edu.cn;syao@jlu.edu.cn
  • 作者简介:宫洵（1987-），男，研究员，博士.研究方向：智能网联自动驾驶汽车控制与优化. E-mail：gongxun@jlu.edu.cn
  • 基金资助:
    国家自然科学基金区域创新发展联合基金项目(U21A20166);国家自然科学基金青年基金项目(62103160);吉林省长春市重大科技专项项目(20220301033GX);吉林省发改委产业技术研究与开发项目(2023C034-3);汽车仿真与控制国家重点实验室自由探索项目

Eco⁃heating control method for connected electric automotive heat pump system in winter conditions

Xun GONG1(),Hang REN1,Hua-lin ZHANG2,Jie-yu WANG1,Yun-feng HU3,4,Yao SUN3()   

  1. 1.School of Artificial Intelligence，Jilin University，Changchun 130012，China
    2.College of Engineering and Technology，Southwest University，Chongqing 400715，China
    3.National Key Laboratory of Automotive Chassis Integration and Bionics，Jilin University，Changchun 130022，China
    4.College of Communication Engineering，Jilin University，Changchun 130012，China
  • Received:2023-06-05 Online:2025-03-01 Published:2025-05-20
  • Contact: Yao SUN E-mail:gongxun@jlu.edu.cn;syao@jlu.edu.cn

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摘要：

为应对冬季寒冷气候条件下车舱供暖需求带来的纯电动汽车“续航焦虑”问题，发掘了车速与热泵空调系统能耗的灵敏度关系，并发展了一种新型的面向控制的热泵空调系统高精度预测模型范式。然后，以此为基础将网联环境下的车速预瞄信息整合到热管理控制器设计中，形成了一种基于模型预测控制（MPC）的预见性生态制热策略（EHS）。最后，将所提出的EHS在基于Dymola的高保真物理仿真模型进行了验证，结果表明：利用车速预瞄信息可以预见性地优化空调系统运行负荷，在满足热舒适度需求的同时，可以相较基准控制器进一步实现18.46%~20.61%的能效提升。

关键词: 控制理论与控制工程, 热泵空调, 模型预测控制, 生态制热

Abstract:

In response to the "range anxiety" issue of battery electric vehicles caused by cabin heating demands in cold winter climate conditions， the sensitivity relationship between vehicle speed and the energy consumption of a heat pump air conditioning system was explored. A new paradigm of a control-oriented high-precision prediction model for the heat pump air conditioning system was developed. Then，based on this model， the vehicle speed preview information provided in the connected environment was integrated into the design of the thermal management controller， creating a predictive eco-heating strategy （EHS） based on model predictive control （MPC）. The proposed EHS was validated using a high-fidelity physical simulation model based on Dymola. The simulation results show that by utilizing vehicle speed preview information to optimize the operation load of the air conditioning system， while satisfying the thermal comfort requirements， it further achieves a 18.46%-20.61% improvement in energy efficiency compared to the baseline controller.

Key words: control theory and control engineering, heat pump air conditioning, model predictive control, eco-heating

中图分类号: 

  • TP273

图1

纯电动汽车热泵空调系统结构图"

表1

热泵空调系统主要元件设计规范"

元件选型及参数
压缩机EffCompressor模块；涡旋式压缩机；排量为6 cm3；最大转速为100 Hz

气体冷

却器

MPET.MoistAirVLEFluid.DetailedCrossFlowHX模块；多孔扁管平行流换热器；材质为铝；总高度为0.45 m；总宽度为0.60 m；总深度为0.015 m；流体层数为1；每层流程数为2；每个流程管道数为｛30，15｝；每个管道的端口数为19；端口直径为1 mm；扁管厚度为1 mm；翅片厚度为0.08 mm；翅片间距为1.2 mm
回热器TubeInTube.VLEFluid.ParallelFlowHX模块；套管式平行流换热器；材质为铝；总长度为0.65 m；翅片厚度为1.5 mm；平行管道数为10
蒸发器MPET.MoistAirVLEFluid.DetailedCrossFlowHX模块；多孔扁管平行流换热器；材质为铝；总高度为0.30 m；总宽度为0.25 m；总深度为0.04 m；流体层数为2；每层流程数为3；每个流程管道数为｛14，14，14｝；每个管道的端口数为19；端口直径为1 mm；扁管厚度为1.5 mm；翅片厚度为0.1 mm；翅片间距为1.5 mm
膨胀阀OrificeValve模块；电子膨胀阀

图2

跨临界循环压焓图"

图3

热泵空调系统车速灵敏度"

表2

车速灵敏度实验中各工况能耗情况"

参数车速/（km·h-1）
020406080100120
能耗/kJ678623512458420396375
节能率/%08.12432384245

每千米能耗/

（kJ·km-1）

—26212985634940

图4

预测模型验证结果"

图5

纯电动汽车热泵空调系统控制策略"

图6

EHS中整合车速灵敏度关系的控制器参数"

图7

基于MPC的生态制热策略闭环仿真结果"

表4

仿真结果"

工况EHS能耗/kJNMPC能耗/kJ节能率/%
CLTC708.79869.2618.46
UDDS575.19712.0519.22
NEDC595.22749.7020.61
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