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KCI Accredited Journals KCI 등재지
KCI Impact Factor 0.54
Journal of the Microelectronics and Packaging Society 2023;30(4):44-49. Published online: Feb, 20, 2024
DOI : doi.org/10.6117/kmeps.2023.30.4.044
In the global pursuit of carbon neutrality, the rapid increase in the adoption of electric vehicles (EVs) has led to a corresponding surge in the demand for batteries. To achieve high efficiency in electric vehicles, considerations of weight reduction and battery safety have become crucial factors. Copper and aluminum, both recognized as lightweight materials, can be effectively joined through laser welding. However, due to the distinct physical characteristics of these two materials, the process of joining them poses technical challenges. This study focuses on conducting simulations to identify the optimal laser parameters for welding copper and aluminum, with the aim of streamlining the welding process. Additionally, a Graphic User Interface (GUI) program has been developed using the Python language to visually present the results. Using machine learning image data, this program is anticipated to predict joint success and serve as a guide for safe and efficient laser welding. It is expected to contribute to the safety and efficiency of the electric vehicle battery assembly process.
Keywords Laser welding, Battery, Random Forest, CFD, Heterojunction