The SOH and RUL of Li-ion batteries can determine the chance of battery management system failure.In this paper,a hybrid model for predicting SOH and RUL is proposed.Firstly,the capacity signal is decomposed using the improved complementary ensemble empirical modal decomposition algorithm with adaptive noise(ICEEMDAN),and then the high-frequency and low-frequency signals are predicted using the SVR algorithm and LSTM,respectively.And at the same time,the SSA is introduced to optimize the SVR parameters to improve the accuracy,and finally,the predicted signals of each component are reorganized as the final prediction results.The simulation results show that all the prediction evaluation indexes are less than 1%on different datasets,and the hybrid prediction model has the advantages of good stability,high accuracy and robustness,which is suitable for predicting the SOH and RUL of batteries.
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