【S020】 先進半導體封裝力學工程論壇

Thursday, 18 November, 14:30 ~ 16:00, Conference Room ROOM 8
Organizer: Hsien-Chie Cheng (鄭仙志), Kuo-Ning Chiang
Chair: 江國寧, 鄭仙志

14:30 ~ 14:45 (15')
0016  Dynamic Electromagnetic-Electro-Thermal Coupled Modeling of Power Conversion System During Load Cycles
Hsien.-Chie Cheng, Yan-Chen Liu and Cong-Jun Huang
The power electronics market in the automotive industry and energy industry witnesses an explosive growth due to growing need of eco-friendly vehicles and drastic climate change and global warming. Power electronics inside a power conversion system, such as insulated-gate bipolar transistor (IGBT) and metal-oxide semiconductor field effect transistor (MOSFET), are the key device determining the efficiency of power conversion. Today, the rapid development of power electronics industry closely follows the trend of the increase in power rating, switching frequency and the decrease of the size, which would unavoidably give rise to high power dissipation density. The high power dissipation density together with harsh operating environment would result in high device temperature, potentially leading to electrical degradation and even breakdown, and thermal-mechanical failure. The objective of the study is to introduce an efficient and effective dynamic multi-physics modeling framework to predict the Electromagnetic-Electro-Thermal coupled behavior of power conversion systems like inverters and converters during load cycles. This modeling framework combines an integrated electromagnetic circuit (E-C) model for exploration of the parasitics parameters and their influence on the switching transients and power losses, and a modified dynamic fully coupled electro-thermal (E-T) model for estimation of instantaneous power loss dependence on instantaneous temperature and device junction temperature. The modified E-T model incorporates a compact thermal model based on Foster network, constructed via parametric computational fluid dynamics (CFD) thermal analysis, and a simple power (P)-temperature (T) relationship, in replace of the time-consuming circuit simulation often used in the conventional dynamic electro-thermal model. The proposed modeling framework is tested on a three-phase inverter operating with a 180-degree conduction mode using six power MOSFET devices as switching devices for brushless DC motor drive during six-step commutation. To validate the proposed E-C model and CFD thermal model, double pulse test and IR thermography experiments are performed, respectively. Besides, the effectiveness of the proposed modeling framework is demonstrated by comparing with the calculated transient device junction temperature with that of the conventional dynamic E-T model. At last, parametric analysis is performed to examine the effects of several key factors on the thermal performance of the inverter.

14:45 ~ 15:00 (15')
0012  車用電子元件之脫層失效分析
Mei-Ling Wu and Jia-Shen Lan
Please refer to the attached file.

15:00 ~ 15:15 (15')
0010  高功率模組封裝製程與可靠度試驗耦合效應之模擬分析與驗證
昌駿 李, 繼元 許 and 元呈 黃

15:15 ~ 15:30 (15')
0052  Deep Learning of the SSL Luminaire Spectral Power Distribution under Multiple Degradation Mechanisms by Hybrid kNN algorithm
Cadmus Yuan and G.Q. Zhang
Solid-state lighting (SSL) is a technology evolution for lighting applications. The high brightness, small size, and white light LED light source drives the enormous development of SSL market. From the mechanical point of view, the failure of the LED packaging, defined by the lumen depreciation or and color shift, is mostly multiple root-cause issues. This is because multiple materials are applied for multiple physical reactions in a single LED packaging.
In this paper, we apply the nonparametric modeling techniques, such as the k-th nearest neighborhood (kNN) method with the Fnn enhancement, and compare its prediction capability with the gate neural network. An average SPD prediction error of approximately 3-5% is observed, with 30 times shorter learning time, comparing to the pure neural network approach