To improve the accuracy and stability of power battery state of charge (SOC) estimation, this book proposes a SOC estimation method for power lithium batteries based on the fusion of deep learning and filtering algorithms. More specifically, the book proposes a SOC estimation method for Li-ion batteries using bi-directional long and short-term memory neural networks (BiLSTM), which overcomes the problem that long and short-term memory neural networks (LSTM) pose, because they can only learn in one direction, resulting in poor feature extraction and memory effect.

The book provides...