Prediction of Remaining Useful Life of Lithium-Ion Batteries Based on PCA-GWO-GRU
In order to improve the accuracy of the GRU neural network model in predicting the remaining useful life(RUL)of lithium-ion batteries,the GRU model was optimized based on PCA-GWO and then applied in the prediction.The results show that compared with the traditional GRU model,the PCA-GWO-GRU model presents higher prediction accuracy.When the starting point of the prediction is 90％of the original data,the prediction accuracy can reach the highest,with the corresponding RMSE of 0.004 9,MAE of 0.003 6,and R2 of 0.986 3.
lithium-ion batteryremaining useful life(RUL)predictionGRUgray wolf optimizer(GWO)principal component analysis(PCA)
万方数据
维普
