마이크로전자및패키징학회지 (Journal of the Microelectronics and Packaging Society)

  • 제30권4호
  • /
  • Pages.44-49
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  • 2023
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  • 1226-9360(pISSN)
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  • 2287-7525(eISSN)
한국마이크로전자및패키징학회 (The Korean Microelectronics and Packaging Society)
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레이저 용접을 이용한 전기차 배터리 이종접합 성공 확률 예측 프로그램 개발에 관한 연구

A Study on the Development of a Program for Predicting Successful Welding of Electric Vehicle Batteries Using Laser Welding

  • 김철환 (부산대학교 광메카트로닉스공학과) ;
  • 문찬수 (부산대학교 광메카트로닉스공학과) ;
  • 이관수 (부산대학교 광메카트로닉스공학과) ;
  • 김진수 (부산대학교 인지메카트로닉스공학과) ;
  • 조애령 ((주)에스티아이씨앤디) ;
  • 신보성 (부산대학교 광메카트로닉스공학과)
  • Cheol-Hwan Kim (Department of Optics and Mechatronics engineering, Pusan National University) ;
  • Chan-Su Moon (Department of Optics and Mechatronics engineering, Pusan National University) ;
  • Kwan-Su Lee (Department of Optics and Mechatronics engineering, Pusan National University) ;
  • Jin-Su Kim (Department of Cogno-Mechatronics Engineering, Pusan National University) ;
  • Ae-Ryeong Jo (Solution Division of Soft-Tech Internationl, Inc) ;
  • Bo-Sung Shin (Department of Optics and Mechatronics engineering, Pusan National University)
  • 투고 : 2023.12.05
  • 심사 : 2023.12.29
  • 발행 : 2023.12.30
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초록

탄소중립을 위한 세계적인 노력 속에서 전기자동차의 사용이 급속하게 증가함에 따라 배터리에 대한 수요도 증가하고 있다. 따라서, 전기자동차의 높은 효율을 달성하기 위해 차체 무게 감소와 배터리에 대한 고려가 중요한 요소로 부각되고 있다. 경량 소재로 알려진 구리와 알루미늄은 레이저 용접을 통해 효과적으로 접합될 수 있다. 그러나 두 소재의 물리적 특성이 서로 다르기 때문에 이를 접합하는 것은 여전히 기술적인 어려움이 존재한다. 본 연구에서는 구리와 알루미늄을 레이저 용접으로 접합하기 위한 최적의 레이저 파라미터를 찾기 위해 시뮬레이션을 수행하였다. 또한, 결과를 시각적으로 제시하기 위해서 Python 언어를 활용하여 GUI(Graphic User Interface) 프로그램을 개발하였다. 이 프로그램은 기계 학습 이미지 데이터를 활용하여 접합 성공을 예측하며, 안전하고 효율적인 레이저 용접 가이드로 활용될 것으로 예상되어, 전기차 배터리 조립 공정의 안전성과 효율성에 기여할 것으로 기대된다.

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.

키워드

과제정보

이 연구는 부산대학교 기본연구지원사업(2년)에 의하여 연구되었음.

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