Nonlinear combination prediction of remaining useful life of automotive Lithium-ion batteries

Due to difficulty of accurately predicting residual life of Lithium batteries with a single prediction model, a nonlinear combination prediction method is proposed in this work．Phase space reconstruction was used to reconstruct data collected from experiments．Reconstructed data were trained and predicted on two single prediction models, improved Elman neural network and nonlinear autoregression neural network．RBF neural network was used to combine predicted values of the two single prediction models, final RUL predicted value was then obtained．The proposed nonlinear combination forecast method of mean square error was found to be nearly 1% higher than PCA-NARX, nearly 2% higher than NARX, nearly 3% higher than improved Elman．Nonlinear combination forecasting method had higher precision and generalization ability．It is conluded that phase space reconstruction technology is helpful to improve prediction precision of nonlinear combination method．