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What is LSTM for Lithium-Ion Battery SoC Estimation about?

This paper presents a novel method for estimating the State of Charge (SoC) of high-capacity lithium-ion battery storage systems using a Long Short-Term Memory (LSTM) neural network. The LSTM model demonstrated superior accuracy compared to traditional Feed-Forward Neural Network (FFNN) and Deep-Feed-Forward Neural Network (DFFNN) models, achieving a maximum standard error of less than 0.62%. The findings indicate that the LSTM approach is effective for real-time monitoring and control of battery management

Author

mrtestfire

Language

EN