State of Charge Prediction of Lithium-Ion Batteries for Electric Aircraft with Swin Transformer

Dear Editor, As an important energy storage device, lithium-ion battery plays a vital role in electric aircrafts, which are new and promising equipment of transportation in the future with low carbon emissions. Accurate prediction of the state of charge (SOC) of lithium-ion batteries is of great importance in reducing the probability of abnormal accidents and ensuring flight safety. This paper proposes a novel Swin Transformer-based method for predicting the SOC of lithium-ion batteries. Firstly, the data are reconstructed and the features are extracted by using interpolation fitting to overcome noise generated by the battery during the data acquisition process in the practical industrial scenarios. Then, the learned features are processed by the Swin Transformer network to achieve accurate SOC prediction of lithium-ion batteries. This letter conducts experiments and verification based on the actual flight data of new energy electric aircrafts. The experimental results show that the proposed method has low prediction error and promising accuracy.