The increasing need for effective energy storage solutions has led to the development of State of Charge (SoC) prediction in batteries as a crucial field of study and research. Accurately estimating SoC is essential for maximizing battery performance and extending longevity in a variety of applications, including grid-scale energy storage and electric car technology. The challenges and emerging approaches related to SoC prediction are examined in this abstract, which includes hybrid, data-driven, and model-based techniques. It also emphasizes how important SoC prediction is for facilitating the mass deployment of renewable energy sources and the shift to a sustainable energy future.
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