Published March 18, 2026 | Version v1
Conference paper Open

Development and optimization of a lightweight LSTM model for battery state-of-charge estimation

Authors/Creators

  • 1. ROR icon Harokopio University of Athens

Description

Accepted version of the paper "Development and optimization of a lightweight LSTM model for battery state-of-charge estimation" presented at the 3rd International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA 2026) on February 7, 2026 by Thalis Paktitis. A final, appropriately paginated version will appear in ieeexplore.com in due course.

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Development and optimization of a lightweight LSTM model for battery state of charge estimation.pdf

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Additional details

Funding

European Commission
PowerizeD - Digitalization of Power Electronic Applications within Key Technology Value Chains 101096387