Resource-efficient artificial intelligence for battery capacity estimation using convolutional FlashAttention fusion networks

Lv, Zhilong; Zhao, Jingyuan

doi:10.1016/j.etran.2024.100383

eTransportation

2025

DOI: 10.1016/j.etran.2024.100383

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Resource-efficient artificial intelligence for battery capacity estimation using convolutional FlashAttention fusion networks

Zhilong Lv,

Jingyuan Zhao

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Battery Prognostics and Health Management: AI and Big Data

Li,

Nan,

Burke

et al. 2024

WEVJ

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In the Industry 4.0 era, integrating artificial intelligence (AI) with battery prognostics and health management (PHM) offers transformative solutions to the challenges posed by the complex nature of battery systems. These systems, known for their dynamic and nonl*-inear behavior, often exceed the capabilities of traditional PHM approaches, which struggle to account for the interplay of multiple physical domains and scales. By harnessing technologies such as big data analytics, cloud computing, the Internet of Things (IoT), and deep learning, AI provides robust, data-driven solutions for capturing and predicting battery degradation. These advancements address long-standing limitations in battery prognostics, enabling more accurate and reliable performance assessments. The convergence of AI with Industry 4.0 technologies not only resolves existing challenges but also introduces innovative approaches that enhance the adaptability and precision of battery health management. This perspective highlights recent progress in battery PHM and explores the shift from traditional methods to AI-powered, data-centric frameworks. By enabling more precise and scalable monitoring and prediction of battery health, this transition marks a significant step forward in advancing the field.

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Battery Prognostics and Health Management: AI and Big Data

Li,

Nan,

Burke

et al. 2024

WEVJ

View full text Add to dashboard Cite

show abstract

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Resource-efficient artificial intelligence for battery capacity estimation using convolutional FlashAttention fusion networks

Cited by 1 publication

References 68 publications

Battery Prognostics and Health Management: AI and Big Data

Battery Prognostics and Health Management: AI and Big Data

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