The proposed intelligent BMS architecture can ensure intelligent control and monitoring of the large-scale battery system. An IBMS is actively modeled to communicate with the battery pack, charging device, user, and cloud platform.
III. IV. The growing demand for electric vehicles (EVs) has created the need for a sophisticated Battery Management System (BMS) to maximize battery performance, safety, and life. This paper proposes an IoT-based BMS with Machine Learning (ML) and Artificial Intelligence (AI) for continous monitoring and predictive maintenance of EV batteries.
The overall architecture of the proposed IBMS is illustrated in Fig. 3. To delve into the multi-layer hierarchy of this intelligent BMS, it consists of three components: end, edge, and cloud. Fig. 3 Comprehensive architecture of the intelligent battery management system (IBMS) illustrating real-time multilayer (end-edge-cloud) communication.
The strong communication architecture of the HAI-BMS makes it easy to connect to other systems and makes it more flexible to work with various types of vehicles. Allowing effective and flexible management of EV battery's output power utilizing an AI-based droop control method is possible.
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