Lithium-Ion UPS Battery Research and Commentary

Wade, John Francis

doi:10.2172/1963149

Cited by 1 publication

(1 citation statement)

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“…It offers principles for information sharing, control capabilities, and interoperability among various microgrid components, promoting effective and dependable operation. • UL 1741: This is a safety standard for inverters, converters, and controllers used in distributed energy systems, especially microgrids (Wade, 2023). It outlines the specifications for these gadgets to guarantee secure and dependable operation when linked to the electrical grid.…”

Section: Distributed Energy Resourcesmentioning

confidence: 99%

A review of battery state of charge estimation and management systems: Models and future prospective

Hussein,

Aghmadi,

Abdelrahman

et al. 2024

WIREs Energy & Environment

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Batteries are considered critical elements in most applications nowadays due to their power and energy density features. However, uncontrolled charging and discharging will negatively affect their functions and might result in a catastrophic failure of their applications. Hence, a battery management system (BMS) is mandated for their proper operation. One of the critical elements of any BMS is the state of charge (SoC) estimation process, which highly determines the needed action to maintain the battery's health and efficiency. Several methods were used to estimate the Lithium‐ion batteries (LIBs) SoC, depending on the LIBs model or any other suitable technique. This article provides a critical review of the existing SoC estimation approaches and the main LIB models with their pros and cons, their possibility to integrate with each other's for precise estimation results, and the applicability of these techniques in electric vehicles and utility applications with the commonly used standards and codes in these sectors. Moreover, this study will also explore a future framework for integrating digital twins (DTs) with BMSs for improved and advanced management. Based on this comprehensive review, it can be concluded that merging the model‐based estimation techniques with the data‐driven approaches with their promising development to determine the dynamic patterns inside the battery can efficiently achieve precise estimation results while reducing the complexity of these models. This integration will align also with the integration of digital twin technology to provide complete and accurate supervision for the BMSs.This article is categorized under: Emerging Technologies > Energy Storage Emerging Technologies > Digitalization Energy and Power Systems > Distributed Generation

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Section: Distributed Energy Resourcesmentioning

confidence: 99%