系统仿真学报 ›› 2016, Vol. 28 ›› Issue (2): 492-497.

• 仿真应用工程 • 上一篇    

用于跨临界CO2汽车空调系统性能优化的控制仿真

赵靖华1,3, 陶晶2,3, 解方喜3, 赵铠楠1   

  1. 1.吉林师范大学计算机学院,吉林 四平 136000;
    2.一汽-法雷奥汽车空调有限公司,长春 130011;
    3.吉林大学汽车工程学院,长春 130025
  • 收稿日期:2014-09-17 修回日期:2014-12-10 出版日期:2016-02-08 发布日期:2020-08-17
  • 作者简介:赵靖华(1980-),男,吉林四平,博士,讲师,研究方向为内燃机工作过程优化与控制;陶晶(1985-),女,吉林长春,硕士,助理研究员,研究方向为汽车空调设计与开发。
  • 基金资助:
    吉林省教育厅“十三五”产业化培育项目

Simulation of Performance Optimization Control about Transcritical CO2 Automotive Air Conditioning System

Zhao Jinghua1,3, Tao Jing2,3, Xie Fangxi3, Zhao Kainan1   

  1. 1. Computer College, Jilin Normal University, Siping 136000, China;
    2. Technology Research and Development, FAW-Valeo Automotive Air Conditioning Co., Ltd., Changchun 130011, China;
    3. College of Automotive Engineering, Jilin University, Changchun 130025, China
  • Received:2014-09-17 Revised:2014-12-10 Online:2016-02-08 Published:2020-08-17

摘要: 根据某企业在研的数据,研究基于AMESim软件建立了跨临界CO2汽车空调系统半理论模型。基于汽车行驶中工况条件多变的实际情况,为使制冷性能系数(COP,Coefficient of Performance)达到最大值,先后从热力学、系统性能分析以及优化控制角度进行了研究。根据火用损失分析和性能分析结果,设计了高压侧压力模糊PID控制器。该控制器能够在系统受到环境温度变化的干扰下,迅速控制制冷剂高压侧压力使系统获得最大COP值;与普通PID控制器的效果对比表明,该控制器的调节时间缩短了200 s,超调量下降了约50%,膨胀阀动作幅度也降低了约40%,控制效果得到了很大改善。

关键词: 汽车空调, CO2, 制冷系数, 模糊控制

Abstract: According to the researching data of certain corporate, a semi-theoretical model of the transcritical CO2 automotive air conditioning system was established using AMESim Software. The research was carried out successively from the aspects of thermodynamics, system performance analysis and optimal control, in order to ensure that the coefficient of performance (COP) reached its maximum. According to the results of exergy loss analysis and performance analysis, the fuzzy PID controller was designed. Under the interference of the ambient temperature change, the controller could control high pressure to ensure COP reach its maximum. The comparison with the well-tuning PID controller shows that the fuzzy PID controller has great improvement in some control performance indicators such as overshoot, settling time and motion range of the implementing agencies, etc.

Key words: automotive air conditions, CO2, coefficient of performance (COP), fuzzy control

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