A long short-term memory network for online state-of-charge estimation of li-ion battery cells

Abstract

This paper proposes a new long short-term memory neural network model to estimate the state-of-charge (SOC) of lithium-ion (Li-ion) battery cells. The proposed model improves the estimation accuracy by accounting for the changes in the battery parameters due to ageing by utilizing relevant knowledge from previous cycles when estimating the current state-of-charge. Derivation and details of the proposed model followed by experimental verification using commercial Li-ion battery cells are provided.