A comprehensive review of energy and battery management system integration: Architectures, approaches, and research directions

초록

The significance of advanced energy and battery management technologies is increasing because of the rapid electrification of transportation and the incorporation of renewable energy sources. Energy management systems (EMSs) and battery management systems (BMSs) are becoming increasingly essential for the safe, dependable, and effective functioning of mobile and stationary energy systems. However, the development of EMS and BMS is often hindered by unrealistic assumptions, inefficient information sharing, and decreased overall system performance. This study provides a comprehensive and systematic review of control algorithms, EMSs, and BMSs, and the latest developments in cloud-computing, artificial intelligence (AI), and the internet of things (IoT). This review emphasizes coordinated EMS-BMS integration and critically examines state estimation methods, digital twins, explainable AI (XAI), and second-life battery management. We analyze the benefits and drawbacks of traditional, optimization-based, and AI-driven control systems and show how coordinated EMS-BMS integration, in contrast to discrete solutions, can enhance system performance, safety, and battery longevity. We identify and discuss the main research gaps, including issues related to interoperability, cybersecurity, real-world validation, and internal state estimation. In light of this critical assessment, we provide important suggestions and future research avenues to guide the creation of reliable, intelligent, and sustainable EMS-BMS systems. This study aligns technological innovation with integrated system design to guide academics and practitioners toward next-generation energy storage management.

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