Frequency-domain temporal transformer networks for state-of-charge estimation of Li-ion batteries
Accurate estimation of the state of charge (SOC) in lithium-ion batteries is crucial for ensuring the safe operation of new energy systems. Existing deep learning methods typically employ recurrent neural networks (RNNs) or Transformer-based architectures to encode temporal dependencies for SOC prediction. However, mos...