• Title/Summary/Keyword: EVs demand

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Battery Module Bonding Technology for Electric Vehicles (전기자동차 배터리 모듈 접합 기술 리뷰)

  • Junghwan Bang;Shin-Il Kim;Yun-Chan Kim;Dong-Yurl Yu;Dongjin Kim;Tae-Ik Lee;Min-Su Kim;Jiyong Park
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.2
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    • pp.33-42
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    • 2023
  • Throughout all industries, eco-friendliness is being promoted worldwide with focus on suppressing the environmental impact. With recent international environment policies and regulations supported by government, the electric vehicles demand is expected to increase rapidly. Battery system itself perform an essential role in EVs technology that is arranged in cells, modules, and packs, and each of them are connected mechanically and electrically. A multifaceted approach is necessary for battery pack bonding technologies. In this paper, pros and cons of applicable bonding technologies, such as resistance welding, laser and ultrasonic bonding used in constructing electric vehicle battery packs were compared. Each bonding technique has different advantages and limitations. Therefore, several criteria must be considered when determining which bonding technology is suitable for a battery cell. In particular, the shape and production scale of battery cells are seen as important factors in selecting a bonding method. While dealing with the types and components of battery cells, package bonding technologies and general issues, we will review suitable bonding technologies and suggest future directions.

The Study for EV Charging Infrastructure connected with Microgrid (마이크로그리드와 연계된 전기자동차 충전인프라에 관한 연구)

  • Hun Shim
    • Journal of Internet of Things and Convergence
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    • v.10 no.1
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    • pp.1-6
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    • 2024
  • In order to increase the use of electric vehicles (EVs) and minimize grid strain, microgrid using renewable energy must take an important role. Microgrid may use fossil fuels such as small diesel power, but in many cases, they can be supplied with energy from renewable energy, which is an eco-friendly energy source. However, renewable energy such as solar and wind power have variable output characteristics. Therefore, in order to meet the charging and discharging energy demands of electric vehicles and at the same time supply load power stably, it is necessary to review the configuration of electric vehicle charging infrastructure that utilizes diesel power or electric vehicle-to-grid (V2G) as a parallel energy source in the microgrid. Against this background, this study modelized a microgrid that can stably supply power to loads using solar power, wind power, diesel power, and V2G. The proposed microgrid uses solar power and wind power generation as the primary supply energy source to respond to power demand, and determines the operation type of the load's electric vehicles and the rotation speed of the load synchronous machine to provide stable power from diesel power for insufficient generations. In order to verify the system performance of the proposed model, we studied the stable operation plan of the microgrid by simulating it with MATLAB /Simulink.

A Study on the Development of a Program for Predicting Successful Welding of Electric Vehicle Batteries Using Laser Welding (레이저 용접을 이용한 전기차 배터리 이종접합 성공 확률 예측 프로그램 개발에 관한 연구)

  • Cheol-Hwan Kim;Chan-Su Moon;Kwan-Su Lee;Jin-Su Kim;Ae-Ryeong Jo;Bo-Sung Shin
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.4
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    • pp.44-49
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    • 2023
  • 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.