焦鸿浩, 唐丽, 朱思雄, 张振越. 微系统热阻模型研究及其应用[J]. 微电子学与计算机, 2022, 39(12): 125-132. DOI: 10.19304/J.ISSN1000-7180.2022.0175
引用本文: 焦鸿浩, 唐丽, 朱思雄, 张振越. 微系统热阻模型研究及其应用[J]. 微电子学与计算机, 2022, 39(12): 125-132. DOI: 10.19304/J.ISSN1000-7180.2022.0175
JIAO Honghao, TANG Li, ZHU Sixiong, ZHANG Zhenyue. Research andapplication of microsystem thermal resistance model[J]. Microelectronics & Computer, 2022, 39(12): 125-132. DOI: 10.19304/J.ISSN1000-7180.2022.0175
Citation: JIAO Honghao, TANG Li, ZHU Sixiong, ZHANG Zhenyue. Research andapplication of microsystem thermal resistance model[J]. Microelectronics & Computer, 2022, 39(12): 125-132. DOI: 10.19304/J.ISSN1000-7180.2022.0175

微系统热阻模型研究及其应用

Research andapplication of microsystem thermal resistance model

  • 摘要: 系统级封装(SIP)实现了高密度、高集成度封装技术,同时散热问题备受关注,热设计中芯片结温预测十分重要.本文采用有限元仿真方法,建立了一种自然对流环境下微系统热阻模型,并通过模型中热阻矩阵预测多芯片总功耗相同条件下的各芯片结温,同时利用热阻测试试验和有限元仿真方法对预测结温进行验证,结果表明热阻矩阵模型预测芯片结温与热阻测试试验和有限元仿真结果误差分别小于2%和5%.但同时发现该热阻矩阵模型的不通用性,对于总功耗变化的多芯片结温,预测结果偏差较大.通过不同总功耗下各热阻矩阵的函数关系建立拟合曲线并修正热阻矩阵模型,修正后的结环境热阻矩阵适用于不同总功率条件、各芯片不同功率条件下的芯片结温预测,预测结果与热阻测试试验中芯片结温和有限元仿真结果误差均小于5%.因此,提出的修正结环境热阻矩阵的方法可以快速且便捷地预测不同功率芯片的结温,并对器件的散热性能进行较为准确的预估.

     

    Abstract: System-in-package realize high-density and high integration packaging technology. At the same time, heat dissipation has attracted much attention. Chip junction temperature prediction is very important in thermal design. In this paper, a micro system thermal resistance model in natural convection environment is established by using the finite element simulation method, and the junction temperature of each chip under the same total power consumption of multiple chips is predicted by the thermal resistance matrix in the model. At the same time, the predicted junction temperature is verified by the thermal resistance test and finite element simulation method. The results show that the error between the thermal resistance matrix model and the thermal resistance test and finite element simulation results is less than 2% and 5% respectively. But at the same time, it is found that the thermal resistance matrix model is not universal. For the multi-chip junction temperature with the change of total power consumption, the prediction result has a large deviation. The fitting curve is established through the functional relationship of each thermal resistance matrix under different total power consumption, and the thermal resistance matrix model is modified. The modified junction environment thermal resistance matrix is suitable for the prediction of chip junction temperature under different total power conditions and different power conditions of each chip. The error between the prediction results and the finite element simulation results of chip junction temperature in thermal resistance test is less than 5%. Therefore, the proposed method of modifying the junction ambient thermal resistance matrix can quickly and conveniently predict the junction temperature of different power chips and accurately predict the heat dissipation performance of devices.

     

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