Search

Article

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

System multi-scale analysis of temperature control for spaceborne electronic devices

Li Xin-Ze Tang Gui-Hua Wang Zi-Han Feng Jian-Chao Zhang Xiao-Feng

Citation:

System multi-scale analysis of temperature control for spaceborne electronic devices

Li Xin-Ze, Tang Gui-Hua, Wang Zi-Han, Feng Jian-Chao, Zhang Xiao-Feng
cstr: 32037.14.aps.73.20240685
PDF
HTML
Get Citation
  • To improve the simulation resolution and accuracy in thermal analysis of spaceborne electronic devices and the temperature control performance of passive thermal control devices, a system multi-scale model is established, thereby obtaining the temperature field and heat flux of electronic devices inside the satellite on different scales as illustrated in the below figure. The temperature fluctuation mechanism inside the satellite is analyzed on different physical scales. The thermal analysis resolution of spaceborne electronic equipment is improved, and a method to reduce the power fluctuation of spaceborne equipment is proposed based on the results of system multi-scale thermal analysis.The results indicate that the accuracy deviation between the multi-scale model of the system and the actual model is less than 9%. However, the system multi-scale model saves 99.67% of the mesh generation time, which greatly improves the computation efficiency. The system multi-scale model can capture the thermal information about device-level chip microstructures at a lower computational cost. The system-level model can evaluate the temperature control and insulation performance of passive thermal control materials on a macroscale. The temperature fluctuation amplitude of the platform compartment is 7.95 K, while the temperature fluctuation amplitude of the load compartment decreases to 2.43 K after the temperature of the composite phase change insulation material has been controlled, which is 69.43% lower than that of the platform compartment. Compared with traditional vacuum insulation panels, the composite phase change materials are very superior in controlling the temperature of the chamber and suppressing temperature fluctuations. The temperature fluctuation signal after being insulated by the composite phase change insulation materials shows a characteristic of shifting to the high-frequency domain. After selecting the cabins that require key insulation and temperature control through multiple regression analysis, a simplified model at device level is employed to obtain temperature fields under different thermal control device layouts as a training dataset. A neural network genetic algorithm is used to predict the optimal installation position of passive thermal control device on the device scale and a thermal control layout scheme is obtained, which reduces the maximum temperature fluctuation of the device by 2.74 K. If the temperature uniformity coefficient is taken as the optimization goal, the temperature of each device on PCB board can be reduced to 14.39% of the average temperature of all devices through optimizations.
      Corresponding author: Tang Gui-Hua, ghtang@mail.xjtu.edu.cn
    • Funds: Project supported by the National Key R&D Program of China (Grant No. 2022YFC2204302).
    [1]

    张嘉麟, 李运泽, 赵欣, 周宇鹏, 魏然 2023 航天器工程 32 53Google Scholar

    Zhang J L, Li Y Z, Zhao X, Zhou Y P, Wei R 2023 S/C. E. 32 53Google Scholar

    [2]

    王定标, 李昂, 吴淇涛, 张浩然, 王晓亮, 王光辉 2023 低温与超导 51 37Google Scholar

    Wang D B, Li A, Wu Q T, Zhang H R, Wang X L, Wang G H 2023 Cryog. Supercond. 51 37Google Scholar

    [3]

    吴利明 2023 硕士学位论文(西安: 长安大学)

    Wu L M 2023 M. S. Thesis (Xi’an: Chang’an University

    [4]

    冯建朝, 张晓峰, 梁鸿, 侍行剑, 何涛, 蔡志鸣 2023 宇航学报 44 132Google Scholar

    Feng J C, Zhang X F, Liang H, Shi X J, He T, Cai Z M 2023 J. Astronaut. 44 132Google Scholar

    [5]

    Mermer E, Ünal R 2023 J Braz. Soc. Mech. Sci. Eng. 45 160.Google Scholar

    [6]

    胡越欣, 张立华, 高永, 魏然, 谭定银, 段会宗, 王丽娇 2022 航天器工程 31 1Google Scholar

    Hu Y X, Zhang L H, Gao Y, Wei R, Tan D Y, Duan H Z, Wang L J 2022 S/C. E. 31 1Google Scholar

    [7]

    陈黎 2017 博士学位论文(西安: 西安交通大学)

    Chen L 2017 Ph. D. Dissertation (Xi’an: Xi’an Jiaotong University

    [8]

    陶文铨 2009 传热与流动问题的多尺度数值模拟: 方法与应用(北京: 科学出版社) 第441页

    Tao W Q 2009 Multiscale Numerical Simulation of Heat Transfer and Flow Problems: Methods and Applications (Beijing: China Science Publishing) p441

    [9]

    丁学凯, 孙立军 2022 ANSYS Icepak 2020 电子散热从入门到精通 (案例实战版) (北京: 电子工业出版社) 第25页

    Ding X K, Sun L J 2022 ANSYS Icepak 2020 Electronics Cooling: From Beginner to Master (Case Study) (Beijing: Publishing House of Electronics Industry) p25

    [10]

    杨世铭, 陶文铨 2006 传热学(第五版) (北京: 高等教育出版社) 第62页

    Yang S M, Tao W Q 2006 Heat transfer (5th Ed.) (Beijing: Higher Education Press) p62

    [11]

    刘红, 张晓峰, 冯建朝, 诸成, 蔡志鸣, 徐雨 2021 空间科学学报 41 337Google Scholar

    Liu H, Zhang X F, Feng J C, Zhu C, Cai Z M, Xu Y 2021 Chin. J. Space Sci. 41 337Google Scholar

    [12]

    魏超 2012 博士学位论文(西安: 西安交通大学)

    Wei C 2012 Ph. D. Dissertation (Xi’an: Xi’an Jiaotong University

    [13]

    赵欣 2008 航天器工程 17 57Google Scholar

    Zhao X 2008 S/C. E. 17 57Google Scholar

    [14]

    Wang Z H, He C B, Hu Y, Tang G H 2024 Sci. China: Technol. Sci. 67 2387Google Scholar

    [15]

    胡和敏, 杜小泽, 杨立军, 杨勇平 2014 动力工程学报 34 216

    Hu H M, Du X Z, Yang L J, Yang Y P 2014 J. Chi. Soc. P E. 34 216

    [16]

    Shao X, Han H, Wang H, Ma J, Hu Y, Li C, Teng H, Chang G, Wang B, Wei Z 2023 Opt. Express 31 32813Google Scholar

    [17]

    同济大学数学系 2017 概率论与数理统计(第四版)(北京: 人民邮电出版社) 第252页

    Tongji University Department of Mathematics 2017 Probability Theory and Mathematical Statistics (Fourth Edition) (Beijing: Posts & Telecommunications Press) p252

    [18]

    程梅苏 2016 硕士学位论文(南京: 南京航空航天大学)

    Cheng M S 2016 M. S. Thesis (Nanjing: Nanjing University of Aeronautics and Astronautics

    [19]

    黄梦真, 朱虹, 刘乃安, 谢小冬, 马超, 张首蕤 2024 工程热物理学报 45 588

    Huang M Z, Zhu H, Liu N A, Xie X D, Ma C, Zhang S R 2024 J. Eng. Thermophys. 45 588

    [20]

    Cho J W, Lee Y J, Kim J H, Hu R, Lee E, Kim S K 2023 ACS Nano 17 10442.Google Scholar

    [21]

    徐志明 2018 博士学位论文 (合肥: 中国科学技术大学)

    Xu Z M 2018 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [22]

    Zhu Z, Wang Z, Liu T, Luo X, Qiu C, Hu R 2023 Cell Rep. Phys. Sci. 4 101540.Google Scholar

    [23]

    夏冰, 陈厚源, 汪一萍, 潘加键, 白伟钢, 常文博, 丁延卫 2021 中山大学学报 60 138Google Scholar

    Xia B, Chen H Y, Wang Y P, Pan J J, Bai W G, Chang W B, Ding Y W 2021 Acta Sci. Nat. Univ. Sunyatseni 60 138Google Scholar

    [24]

    王永康 2015 ANSYS Icepak 电子散热基础教程(北京: 国防工业出版社) 第30页

    Wang Y K 2015 ANSYS Icepak Electronics Cooling Fundamentals Tutorial (Beijing: National Defense Industry Press) p30

    [25]

    朱文博 2023 硕士学位论文(长春: 中国科学院长春光学精密机械与物理研究所)

    Zhu W B 2023 M. S. Thesis (Changchun: Changchun Institute of Optics, Fine Mechanicsand Physics, Chinese Academy of Sciences

    [26]

    李运泽, 魏传锋, 袁领双, 王浚 2005 北京航空航天大学学报 60 372Google Scholar

    Li Y Z, Wei C F, Yuan L S, Wang J 2005 J. Beijing Univ. Aeronaut. Astronaut. 60 372Google Scholar

    [27]

    余志豪 2022 硕士学位论文 (哈尔滨: 哈尔滨工业大学)

    Yu Z H 2022 M. S. Thesis (Harbin: Harbin Institute of Technology

  • 图 1  太极卫星多尺度热分析技术路线与研究内容

    Figure 1.  Schematic of multi-scale thermal analysis and research contents of Taiji satellite.

    图 2  星载PCB板发热元件分布

    Figure 2.  Distribution of heating sources on spaceborne circuit board.

    图 3  芯片细微结构温度场 (a) PQFP芯片细微结构温度云图; (b) QFP芯片细微结构温度云图

    Figure 3.  Temperature field of fine chip structure: (a) Temperature cloud map of PQFP fine chip structure; (b) temperature cloud map of QFP fine chip structure.

    图 4  太极卫星系统级热分析模型

    Figure 4.  System-level thermal analysis model of Taiji satellite.

    图 5  卫星不同舱室温度结果 (a) 复合相变材料方案时域响应; (b) 真空隔热板方案时域响应; (c) 复合相变材料方案频域响应; (d) 真空隔热板方案频域响应

    Figure 5.  Temperature results of different satellite cabins: (a) Time domain response of composite phase change material scheme; (b) time domain response of vacuum insulation board scheme; (c) frequency domain response of composite phase change material scheme; (d) frequency domain response of vacuum insulation board scheme.

    图 6  温度信号傅里叶分解图 (a) 复合相变隔热材料方案; (b) 真空隔热板方案

    Figure 6.  Fourier exploded plot of temperature signal: (a) Composite phase change insulation material scheme; (b) vacuum insulation board scheme.

    图 7  平台舱室编号示意图

    Figure 7.  Schematic of platform cabin.

    图 8  不同热控布局方案指标分布图 (a) 不同热控布局电路板最高温度波动; (b)不同热控布局电路板温度均匀系数

    Figure 8.  Indicators for different thermal control layouts: (a) Maximum temperature fluctuation of the circuit board in different thermal control layouts; (b) temperature uniformity coefficient of circuit boards in different thermal control layouts.

    图 9  系统多尺度优化设计技术路线图

    Figure 9.  Schematic of system multi-scale optimization.

    表 1  主要发热元件功率参数

    Table 1.  Power parameters of main heating sources.

    发热元件元件尺寸/mm3封装类型发热参数/W
    芯片140×40×2PQFP0.5
    芯片2—芯片726×26×2.15PBGA0.1
    芯片830×30×1.25QFP0.3
    DownLoad: CSV

    表 2  不同建模方法结果的精度对比

    Table 2.  Accuracy comparison of results from different modeling methods.

    评价指标系统多尺度/℃全场密网格/℃相对误差/%
    芯片1103.13399.7223.307
    芯片283.00981.6381.651
    芯片383.05881.6831.655
    芯片481.89481.2140.830
    芯片582.02180.5241.825
    芯片682.58080.6472.341
    芯片781.59680.2301.674
    芯片897.29088.7478.781
    DownLoad: CSV

    表 3  不同建模方法的网格统计信息

    Table 3.  Grid information of different modeling methods.

    评价指标系统多尺度全场密网格
    系统级器件级
    网格数量/个1091812531610884559
    最大网格尺寸/mm12112.5
    最低面对齐率0.610.05
    网格生成时间/min<1300
    DownLoad: CSV

    表 4  复合相变隔热材料热物性参数

    Table 4.  Thermophysical properties of composite phase change thermal insulation materials.

    隔热层 密度
    ρ/(kg·m–3)
    热导率 λ
    /(W·m–1·K–1)
    比热容 cp
    /(J·kg–1·K–1)
    相变材料1 900 2.95 2350
    隔热材料 114 0.04 500
    相变材料2 1500 12.53 2350
    DownLoad: CSV

    表 5  隔热舱室多元回归分析结果

    Table 5.  Multiple regression analysis results of insulated cabins.

    平台舱室编号显著性共线性统计
    14.8×10–54.797
    20.7571.066
    30.1181.039
    44.47×10–121.035
    54.18×10–45.245
    60.0144.685
    DownLoad: CSV
  • [1]

    张嘉麟, 李运泽, 赵欣, 周宇鹏, 魏然 2023 航天器工程 32 53Google Scholar

    Zhang J L, Li Y Z, Zhao X, Zhou Y P, Wei R 2023 S/C. E. 32 53Google Scholar

    [2]

    王定标, 李昂, 吴淇涛, 张浩然, 王晓亮, 王光辉 2023 低温与超导 51 37Google Scholar

    Wang D B, Li A, Wu Q T, Zhang H R, Wang X L, Wang G H 2023 Cryog. Supercond. 51 37Google Scholar

    [3]

    吴利明 2023 硕士学位论文(西安: 长安大学)

    Wu L M 2023 M. S. Thesis (Xi’an: Chang’an University

    [4]

    冯建朝, 张晓峰, 梁鸿, 侍行剑, 何涛, 蔡志鸣 2023 宇航学报 44 132Google Scholar

    Feng J C, Zhang X F, Liang H, Shi X J, He T, Cai Z M 2023 J. Astronaut. 44 132Google Scholar

    [5]

    Mermer E, Ünal R 2023 J Braz. Soc. Mech. Sci. Eng. 45 160.Google Scholar

    [6]

    胡越欣, 张立华, 高永, 魏然, 谭定银, 段会宗, 王丽娇 2022 航天器工程 31 1Google Scholar

    Hu Y X, Zhang L H, Gao Y, Wei R, Tan D Y, Duan H Z, Wang L J 2022 S/C. E. 31 1Google Scholar

    [7]

    陈黎 2017 博士学位论文(西安: 西安交通大学)

    Chen L 2017 Ph. D. Dissertation (Xi’an: Xi’an Jiaotong University

    [8]

    陶文铨 2009 传热与流动问题的多尺度数值模拟: 方法与应用(北京: 科学出版社) 第441页

    Tao W Q 2009 Multiscale Numerical Simulation of Heat Transfer and Flow Problems: Methods and Applications (Beijing: China Science Publishing) p441

    [9]

    丁学凯, 孙立军 2022 ANSYS Icepak 2020 电子散热从入门到精通 (案例实战版) (北京: 电子工业出版社) 第25页

    Ding X K, Sun L J 2022 ANSYS Icepak 2020 Electronics Cooling: From Beginner to Master (Case Study) (Beijing: Publishing House of Electronics Industry) p25

    [10]

    杨世铭, 陶文铨 2006 传热学(第五版) (北京: 高等教育出版社) 第62页

    Yang S M, Tao W Q 2006 Heat transfer (5th Ed.) (Beijing: Higher Education Press) p62

    [11]

    刘红, 张晓峰, 冯建朝, 诸成, 蔡志鸣, 徐雨 2021 空间科学学报 41 337Google Scholar

    Liu H, Zhang X F, Feng J C, Zhu C, Cai Z M, Xu Y 2021 Chin. J. Space Sci. 41 337Google Scholar

    [12]

    魏超 2012 博士学位论文(西安: 西安交通大学)

    Wei C 2012 Ph. D. Dissertation (Xi’an: Xi’an Jiaotong University

    [13]

    赵欣 2008 航天器工程 17 57Google Scholar

    Zhao X 2008 S/C. E. 17 57Google Scholar

    [14]

    Wang Z H, He C B, Hu Y, Tang G H 2024 Sci. China: Technol. Sci. 67 2387Google Scholar

    [15]

    胡和敏, 杜小泽, 杨立军, 杨勇平 2014 动力工程学报 34 216

    Hu H M, Du X Z, Yang L J, Yang Y P 2014 J. Chi. Soc. P E. 34 216

    [16]

    Shao X, Han H, Wang H, Ma J, Hu Y, Li C, Teng H, Chang G, Wang B, Wei Z 2023 Opt. Express 31 32813Google Scholar

    [17]

    同济大学数学系 2017 概率论与数理统计(第四版)(北京: 人民邮电出版社) 第252页

    Tongji University Department of Mathematics 2017 Probability Theory and Mathematical Statistics (Fourth Edition) (Beijing: Posts & Telecommunications Press) p252

    [18]

    程梅苏 2016 硕士学位论文(南京: 南京航空航天大学)

    Cheng M S 2016 M. S. Thesis (Nanjing: Nanjing University of Aeronautics and Astronautics

    [19]

    黄梦真, 朱虹, 刘乃安, 谢小冬, 马超, 张首蕤 2024 工程热物理学报 45 588

    Huang M Z, Zhu H, Liu N A, Xie X D, Ma C, Zhang S R 2024 J. Eng. Thermophys. 45 588

    [20]

    Cho J W, Lee Y J, Kim J H, Hu R, Lee E, Kim S K 2023 ACS Nano 17 10442.Google Scholar

    [21]

    徐志明 2018 博士学位论文 (合肥: 中国科学技术大学)

    Xu Z M 2018 Ph. D. Dissertation (Hefei: University of Science and Technology of China

    [22]

    Zhu Z, Wang Z, Liu T, Luo X, Qiu C, Hu R 2023 Cell Rep. Phys. Sci. 4 101540.Google Scholar

    [23]

    夏冰, 陈厚源, 汪一萍, 潘加键, 白伟钢, 常文博, 丁延卫 2021 中山大学学报 60 138Google Scholar

    Xia B, Chen H Y, Wang Y P, Pan J J, Bai W G, Chang W B, Ding Y W 2021 Acta Sci. Nat. Univ. Sunyatseni 60 138Google Scholar

    [24]

    王永康 2015 ANSYS Icepak 电子散热基础教程(北京: 国防工业出版社) 第30页

    Wang Y K 2015 ANSYS Icepak Electronics Cooling Fundamentals Tutorial (Beijing: National Defense Industry Press) p30

    [25]

    朱文博 2023 硕士学位论文(长春: 中国科学院长春光学精密机械与物理研究所)

    Zhu W B 2023 M. S. Thesis (Changchun: Changchun Institute of Optics, Fine Mechanicsand Physics, Chinese Academy of Sciences

    [26]

    李运泽, 魏传锋, 袁领双, 王浚 2005 北京航空航天大学学报 60 372Google Scholar

    Li Y Z, Wei C F, Yuan L S, Wang J 2005 J. Beijing Univ. Aeronaut. Astronaut. 60 372Google Scholar

    [27]

    余志豪 2022 硕士学位论文 (哈尔滨: 哈尔滨工业大学)

    Yu Z H 2022 M. S. Thesis (Harbin: Harbin Institute of Technology

  • [1] Wang Chen-Yang, Duan Qian-Qian, Zhou Kai, Yao Jing, Su Min, Fu Yi-Chao, Ji Jun-Yang, Hong Xin, Liu Xue-Qin, Wang Zhi-Yong. A hybrid model for photovoltaic power prediction of both convolutional and long short-term memory neural networks optimized by genetic algorithm. Acta Physica Sinica, 2020, 69(10): 100701. doi: 10.7498/aps.69.20191935
    [2] Yuan Lin, Yang Xue-Song, Wang Bing-Zhong. Prediction of time reversal channel with neural network optimized by empirical knowledge based genetic algorithm. Acta Physica Sinica, 2019, 68(17): 170503. doi: 10.7498/aps.68.20190327
    [3] Lin Fei-Fei, Zeng Zhe-Zhao. Synchronization of uncertain fractional-order chaotic systems with time delay based on adaptive neural network control. Acta Physica Sinica, 2017, 66(9): 090504. doi: 10.7498/aps.66.090504
    [4] Xia Ge, Yang Li, Kou Wei, Du Yong-Cheng. Design and research of columnar thermal cloak with arbitrary shape in inhomogeneous backgrounds. Acta Physica Sinica, 2017, 66(11): 114401. doi: 10.7498/aps.66.114401
    [5] Zeng Zhe-Zhao. Feedback compensation control on chaotic system with uncertainty based on radial basis function neural network. Acta Physica Sinica, 2013, 62(3): 030504. doi: 10.7498/aps.62.030504
    [6] Miao Zhi-Qiang, Wang Yao-Nan. Robust adaptive radial wavelet neural network control for chaotic systems using backstepping design. Acta Physica Sinica, 2012, 61(3): 030503. doi: 10.7498/aps.61.030503
    [7] Li Hua-Qing, Liao Xiao-Feng, Huang Hong-Yu. Synchronization of uncertain chaotic systems based on neural network and sliding mode control. Acta Physica Sinica, 2011, 60(2): 020512. doi: 10.7498/aps.60.020512
    [8] Zhang Min, Hu Shou-Song. Adaptive control of uncertain chaotic systems with time delays using dynamic structure neural network. Acta Physica Sinica, 2008, 57(3): 1431-1438. doi: 10.7498/aps.57.1431
    [9] Feng Chao-Wen, Cai Li, Li Qin. Implementation and application of cellular neural networks based on single electron device. Acta Physica Sinica, 2008, 57(4): 2462-2467. doi: 10.7498/aps.57.2462
    [10] Niu Pei-Feng, Zhang Jun, Guan Xin-Ping. Research on genetic algorithm optimization based on PID control with two degrees of freedom controller for chaotic system. Acta Physica Sinica, 2007, 56(7): 3759-3765. doi: 10.7498/aps.56.3759
    [11] Niu Pei_Feng, Zhang Jun, Guan Xin_Ping. Research on a proportional-integral-derivative neural network decoupling control based on genetic algorithm optimization for unified chaotic system. Acta Physica Sinica, 2007, 56(5): 2493-2497. doi: 10.7498/aps.56.2493
    [12] Sima Wen-Xia, Liu Fan, Sun Cai-Xin, Liao Rui-Jin, Yang Qing. Chaos control of ferroresonance system based on improved RBF neural network. Acta Physica Sinica, 2006, 55(11): 5714-5720. doi: 10.7498/aps.55.5714
    [13] Yu Ling-Hui, Fang Jian-Cheng. Synchronization of chaotic neural networks based on adaptive inverse control and its applications in secure communications. Acta Physica Sinica, 2005, 54(9): 4012-4018. doi: 10.7498/aps.54.4012
    [14] Wang Dong-Feng. Genetic algorithm optimization based proportional-integral-derivative controller for unified chaotic system. Acta Physica Sinica, 2005, 54(4): 1495-1499. doi: 10.7498/aps.54.1495
    [15] Wu Zhong-Qiang, Ao Dun, Liu Kun. Fuzzy control of a chaotic system based on genetic algorithm. Acta Physica Sinica, 2004, 53(1): 21-24. doi: 10.7498/aps.53.21
    [16] Liu Ding, Ren Hai-Peng, Kong Zhi-Qiang. Control of chaos solely based on RBF neural network without an analytical model. Acta Physica Sinica, 2003, 52(3): 531-535. doi: 10.7498/aps.52.531
    [17] Wang Yao-Nan, Tan Wen. Genetic-based neural network control for chaotic system. Acta Physica Sinica, 2003, 52(11): 2723-2728. doi: 10.7498/aps.52.2723
    [18] Ren Hai-Peng, Liu Ding. . Acta Physica Sinica, 2002, 51(5): 982-987. doi: 10.7498/aps.51.982
    [19] Tan Wen, Wang Yao-Nan, Liu Zhu-Run, Zhou Shao-Wu. . Acta Physica Sinica, 2002, 51(11): 2463-2466. doi: 10.7498/aps.51.2463
    [20] HE GUO-GUANG, CAO ZHI-TONG. CONTROLLING CHAOS IN CHAOTIC NEURAL NETWORK. Acta Physica Sinica, 2001, 50(11): 2103-2107. doi: 10.7498/aps.50.2103
Metrics
  • Abstract views:  892
  • PDF Downloads:  31
  • Cited By: 0
Publishing process
  • Received Date:  14 May 2024
  • Accepted Date:  04 August 2024
  • Available Online:  23 August 2024
  • Published Online:  20 September 2024

/

返回文章
返回