Study on Applying Masterless BMS Architecture to Improve Safety of Propulsion ESS for Railway Vehicles

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..