主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

汽车实用技术 ›› 2025, Vol. 50 ›› Issue (15): 7-11.DOI: 10.16638/j.cnki.1671-7988.2025.015.002

• 新能源汽车 • 上一篇    

纯电动重型汽车集成热管理系统仿真 与试验验证

李思思,温逸伦,孙坤   

  1. 陕西重型汽车有限公司 汽车工程研究院
  • 发布日期:2025-08-08
  • 通讯作者: 李思思
  • 作者简介:李思思(1990-),女,硕士,工程师,研究方向为热管理仿真分析

Simulation and Experimental Validation of the Integrated Thermal Management System for an Electric Heavy-Duty Vehicle

LI Sisi, WEN Yilun, SUN Kun   

  1. Institute of Automotive Engineering, Shaanxi Heavy Duty Automobile Company Limited
  • Published:2025-08-08
  • Contact: LI Sisi

摘要: 纯电动重型汽车正朝着高功率、长续航、轻量化与智能化方向迅速发展。基于 AMESim 软件,构建了一套完整的纯电动重型汽车集成热管理系统仿真模型。该模型涵盖了电池热管 理模型、驾驶舱热舒适模型、空调回路模型以及比例-积分(PI)控制模型,能够真实反映各 部件的动态响应。对关键部件进行了仿真标定,其精度均达 85%以上。利用高精度部件搭建 热管理系统模型,仿真结果与实车试验数据进行了对比分析,系统在压缩机转速控制、驾驶 舱平均温度、电池入口水温等关键性能指标上均满足设计要求,仿真精度高达 85%。研究验 证了 AMESim 平台在集成热管理系统建模与控制策略开发中的可行性与有效性,为后续控制 策略优化及实车试验验证提供了坚实的技术基础和数据支撑。

关键词: 纯电动重型汽车;集成热管理系统;一维仿真分析;仿真精度;AMESim

Abstract: Electric heavy-duty vehicles are rapidly evolving toward high power, long range, lightweight design, and intelligent functionality. Based on the AMESim software platform, a comprehensive simulation model of an integrated thermal management system for electric heavy-duty vehicles is developed. This model includes a battery thermal management module, a cabin thermal comfort module, an air conditioning loop model and a proportional-integral (PI) control module, effectively capturing the dynamic responses of each component. Key components are calibrated through simulation, achieving an accuracy of over 85%. Using these high-precision components, the thermal management system model is constructed and validated through comparison with real vehicle test data. The system meets design requirements in key performance indicators such as compressor speed control, average cabin temperature, and battery inlet coolant temperature, with a simulation accuracy reaching 85%. The study confirms the feasibility and effectiveness of the AMESim platform for modeling integrated thermal management systems and developing control strategies, providing a solid technical foundation and data support for future control optimization and vehicle testing.

Key words: electric heavy-duty vehicle; integrated thermal management system; 1D simulation analysis; simulation accuracy; AMESim