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논문 기본 정보

저자정보
(Korea National University of Transportation) (Korea Railroad Research Institute) (Korea Railroad Research Institute) (Korea National University of Transportation)
저널정보
대한전기학회 전기학회논문지 전기학회논문지 제73권 제12호
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    초록·키워드

    Conventional Slave-Master structured Battery Management Systems(BMS) face limitations due to the inherent constraints of their wired architecture. Also, the aging characteristics of propulsion lithium-ion batteries, which require management, vary depending on the operating environment and output conditions. When these limitations occur simultaneously, conventional BMS monitoring and control functions become inadequate for accurate fire risk prediction and effective safety management. So, we propose a Masterless BMS to overcome these limitations. The proposed BMS efficiently processes large volumes of battery data through wireless communication and enables sophisticated battery management through Artificial Intelligence(AI)-based battery state estimation using an external server. This paper analyzes efficient operational methods and optimal design approaches for applying a Masterless BMS architecture to propulsion Energy Storage Systems(ESS) for railway vehicles..

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      UCI(KEPA) : I410-151-25-02-092309299