基于Dymola的汽车空调系统性能仿真分析
Performance Simulation Analysis of Automobile Air Conditioning System Based on Dymola
DOI: 10.12677/MOS.2023.123299, PDF,    科研立项经费支持
作者: 汪本源*, 武卫东#, 王烽先, 朱群东, 黄逸宸：上海理工大学能源与动力工程学院，上海
关键词: 汽车空调；Dymola；系统仿真；性能分析；Automotive Air-Conditioning； Dymola； System Simulation； Performance Analysis
摘要: 为了解决汽车空调系统仿真涉及多领域耦合的问题，本文运用Dymola仿真非因果性建模、层级化建模、多领域建模等特点，搭建了一套汽车空调系统仿真模型，与实验数据对比分析了不同极端工况及多参数变化下仿真计算的准确性，利用仿真模型定量分析了不同因素对系统性能的影响。结果表明：仿真计算得到的换热性能与对应实验值之间的平均误差在±7%以内；车内环境温度每升高1℃、蒸发器进风风量每增加50 m3/h、车外换热器进风风速每增加0.5 m/s或车外环境温度每降低1℃，制冷量分别提高了2.4%、1.9%、0.4%、0.8%；系统能效比分别提高了1.6%、6.3%、4.0%和3.1%。
Abstract: To solve the problem of multi-domain coupling involved in the simulation of automobile air condi-tioning system, this paper was used Dymola simulation non-causal modeling, hierarchical modeling, multi-domain modeling and other characteristics to build a set of automobile air conditioning sys-tem simulation model. Compared with the experimental data, the accuracy of the simulation calcu-lation under different extreme conditions and multi-parameter change coverage was analyzed, and the influence of different factors on the system performance was quantitatively analyzed by using the simulation model. The results showed that the average error between the simulated heat transfer performance and the corresponding experimental value was within ±7%. The cooling ca-pacity increased by 2.4%, 1.9%, 0.4%, and 0.8% respectively, when the in-vehicle ambient tem-perature rose by 1˚C, the evaporator air flow rate increased by 50 m3/h, the external heat exchang-er air velocity increased by 0.5 m/s or the external ambient temperature decreased by 1˚C. Addi-tionally, the system coefficient of performance is improved by 1.6%, 6.3%, 4.0%, and 3.1% respec-tively.
文章引用：汪本源, 武卫东, 王烽先, 朱群东, 黄逸宸. 基于Dymola的汽车空调系统性能仿真分析[J]. 建模与仿真, 2023, 12(3): 3251-3260. https://doi.org/10.12677/MOS.2023.123299

参考文献

[1] Zhang, X. and Bai, X. (2017) Incentive Policies from 2006 to 2016 and New Energy Vehicle Adoption in 2010-2020 in China. Renewable & Sustainable Energy Reviews, 70, 24-43. [Google Scholar] [CrossRef] 
[2] 杨仕稼. 电动汽车空调系统性能系数及压缩机性能分析[J]. 制冷技术, 2019, 39(3): 46-51.
[3] 雷良新, 陶乐仁, 孙悦, 等. 纯电动汽车乘员舱冬季热负荷特性研究[J]. 制冷技术, 2022, 42(1): 65-70.
[4] Zhang, Z., Wang, J., Feng, X., et al. (2018) The Solu-tions to Electric Vehicle Air Conditioning Systems: A Review. Renewable & Sustainable Energy Reviews, 91, 443-463. [Google Scholar] [CrossRef] 
[5] Du, Z., Lin, B. and Guan, C. (2019) Development Path of Electric Vehicles in China under Environmental and Energy Security Constraints. Resources, Conservation and Recycling, 143, 17-26. [Google Scholar] [CrossRef] 
[6] Li, H.-J., Zhou, G.-H., Li, A., et al. (2014) Heat Pump Air Condi-tioning System for Pure Electric Vehicle at Ultra-Low Temperature. Thermal Science, 18, 1667-1672. [Google Scholar] [CrossRef] 
[7] Zhou, G., Li, H., Liu, E., et al. (2017) Experimental Study on Combined De-frosting Performance of Heat Pump Air Conditioning System for Pure Electric Vehicle in Low Temperature. Applied Thermal Engineering, 116, 677-684. [Google Scholar] [CrossRef] 
[8] 陈鸿明, 钱锐, 李华. 汽车空调系统仿真自动优化平台研究[J]. 制冷技术, 2019, 39(4): 53-58.
[9] 孙港国, 魏名山, 郑思宇, 宋盼盼. 纯电动汽车空调与电池综合热管理仿真研究[J]. 制冷技术, 2022, 42(2): 12-18.
[10] 闵海涛, 曹云波, 曾小华, 徐星. 电动汽车空调系统建模及对整车性能的影响[J]. 吉林大学学报(工学版), 2009, 39(S1): 53-57.
[11] Zhang, H., Dai, L., Xu, G., et al. (2009) Studies of Air-Flow and Temperature Fields Inside a Passenger Compartment for Improving Thermal Comfort and Saving Energy. Part I: Test/Numerical Model and Validation. Applied Thermal Engineering, 29, 2022-2027. [Google Scholar] [CrossRef] 
[12] 靳永言. 汽车空调两器(冷凝器与蒸发器)与系统的建模与仿真[D]: [硕士学位论文]. 西安: 长安大学, 2019.
[13] Ibrahim, S. and Mehta, R.C. (2018) An Investigation of Air Flow and Thermal Comfort of Modified Conventional Car Cabin Using Computational Fluid Dynamics. Journal of Applied Fluid Mechanics, 11, 141-150. [Google Scholar] [CrossRef] 
[14] 王耀凯. 基于Modelica的纯电动客车动力系统建模、仿真和优化[D]: [硕士学位论文]. 郑州: 郑州大学, 2017.
[15] 朱涛. 基于Dymola的电动车热管理系统模块化建模与集成仿真[D]: [硕士学位论文]. 长春: 吉林大学, 2017.
[16] 黄锡昌, 宗志坚, 陈承鹤, 查鸿山. 基于Modelica的电动汽车电池建模与仿真[J]. 计算机工程与设计, 2012, 33(5): 2073-2077.
[17] Hirano, Y. (2019) JSAE-SICE BENCHMARK PROBLEm for Vehicle Dynamics Control. Control Theory and Technology, 17, 131-137. [Google Scholar] [CrossRef] 
[18] Tummescheit, H., Eborn, J. and Prölss, K. (2005) Airconditioning—A Modelica Library for Dynamic Simulation of AC Systems.
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.151.5654&rep=rep1&type=pdf
[19] Desideri, A., Her-nandez, A., et al. (2016) Steady-State and Dynamic Validation of a Small-Scale Waste Heat Recovery System Using the Ther-moCycle Modelica Library. Energy, 115, 684-696. [Google Scholar] [CrossRef] 
[20] 陈雪平, 张海亮, 钟再敏, 陈辛波. 插电式混合动力汽车能耗及其影响因素分析[J]. 同济大学学报(自然科学版), 2016, 44(11): 1749-1754.
[21] Cvok, I., Ratković, I. and Deur, J. (2020) Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems. Energies, 13, Article No. 5131. [Google Scholar] [CrossRef] 
[22] 薛庆峰, 张晓强, 邹慧明, 田长青. 流道布局对微通道平行流车外换热器性能的影响[J]. 汽车技术, 2018, 2023(1): 25-30.
[23] 杜琳, 周黎旸, 陈琪, 等. 微通道平行流换热器分配特性及优化研究[J]. 制冷学报, 2021, 42(5): 111-117.
[24] Ezzatneshan, E. and Goharimehr, R. (2021) A Pseudopotential Lattice Boltzmann Method for Simulation of Two-Phase Flow Transport in Porous Medium at High-Density and High-Viscosity Ratios. Geofluids, 2021, Article ID: 5668743. [Google Scholar] [CrossRef] 
[25] Sundén, B. (2017) Chapter Two—Advanced Heat Transfer Topics in Complex Duct Flows. In: Sparrow, E.M., Abraham, J.P. and Gorman, J.M., Eds., Advances in Heat Transfer, Vol. 49, Elsevier, Am-sterdam, 37-89. [Google Scholar] [CrossRef] 
[26] He, Y., Ren, A., Tang, T. and Wang, T. (2022) Multi-Scale Numerical Simulation of Flow, Heat and Mass Transfer Behaviors in Dense Gas-Solid Flows: A Brief Review. Journal of Thermal Sci-ence, 31, 607-633. [Google Scholar] [CrossRef] 

为你推荐