TY - GEN
T1 - Research on Multi-Chip Modules Device Junction Temperature Prediction Method
AU - Liu, Jiahao
AU - Tian, Dongyang
AU - Qiu, Lijin
AU - Chen, Fangzhou
AU - Huang, Zibin
AU - Zhang, Jinghui
AU - Chen, Hongtao
AU - Zhao, Hao
AU - Chen, Rui
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - As the package size of Multi-Chip Modules continues to decrease and power density continues to increase, the junction temperature of the chip rises sharply. Accurately predicting the junction temperature of chips during service is of great significance in order to meet the requirements of chip heat dissipation and reliability. After fully considering the thermal coupling effect, this paper uses a thermal resistance network model, thermal simulation, and thermal resistance matrix to calculate the junction temperature of a Multi-Chip Modules device. Meanwhile, the results mentioned above were verified by the measured results. The results indicate that the relative error between the calculated and measured results obtained by the three methods is less than 10 %. The results indicate that all three methods can efficiently and accurately predict the junction temperature of Multi-Chip Modules devices. In addition, the prediction accuracy of the three methods, in descending order, is thermal resistance matrix, thermal simulation, and thermal resistance network model.
AB - As the package size of Multi-Chip Modules continues to decrease and power density continues to increase, the junction temperature of the chip rises sharply. Accurately predicting the junction temperature of chips during service is of great significance in order to meet the requirements of chip heat dissipation and reliability. After fully considering the thermal coupling effect, this paper uses a thermal resistance network model, thermal simulation, and thermal resistance matrix to calculate the junction temperature of a Multi-Chip Modules device. Meanwhile, the results mentioned above were verified by the measured results. The results indicate that the relative error between the calculated and measured results obtained by the three methods is less than 10 %. The results indicate that all three methods can efficiently and accurately predict the junction temperature of Multi-Chip Modules devices. In addition, the prediction accuracy of the three methods, in descending order, is thermal resistance matrix, thermal simulation, and thermal resistance network model.
KW - Junction temperature
KW - Numerical simulation
KW - Prediction method
KW - Thermal resistance
UR - https://www.scopus.com/pages/publications/105030081460
U2 - 10.1109/ICRMS65480.2025.00088
DO - 10.1109/ICRMS65480.2025.00088
M3 - 会议稿件
AN - SCOPUS:105030081460
T3 - Proceedings - 2025 16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025
SP - 478
EP - 483
BT - Proceedings - 2025 16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025
Y2 - 27 July 2025 through 30 July 2025
ER -