State of Charge Estimation Model for Lithium-ion Batteries Based on Deep Learning Neural Networks.

As a new generation of high-performance batteries, lithium-ion batteries have found extensive applications in electric cars, as well as energy storage systems and various other industries. State of charge (SOC) estimation is one of the most important indicators. SOC estimation model of lithium-ion battery based on deep learning neural networks employs diverse external measurement parameters and internal battery parameters as input information, and adopts feed-forward neural network (FNN), convolutional neural network (CNN) and long short-term memory network (LSTM) as predictors to realize the accurate SOC estimation. The model based on deep learning neural networks takes into account the influence of various input parameters and can understand the state of the battery more comprehensively. By using FNN, CNN and LSTM networks, the influence of noise and instability of battery data on SOC estimation can be effectively avoided. After many times of training and verification, the high accuracy and stability of the model can meet the need of SOC estimation for lithium-ion batteries. [ABSTRACT FROM AUTHOR]