Lithium-ion Battery Remaining Life Prediction Method Based on Hybrid Algorithm

Lithium-ion batteries remaining life is an important index for evaluating the remaining value of the retired Lithium-ion batteries, and the prediction algorithm plays a crucial role. An efficient estimation method can obtain the remaining life of Lithium-ion batteries and prevent potential batteries safety issues. Different from the traditional Lithium-ion battery life prediction methods which require the empirical models and construction of a battery management model, in this art, a data-driven algorithm is proposed to predict the remaining life of Lithium-ion batteries. The Elman network and the differential evolution method are fused for ensuring the prediction accuracy and stability, and the experiments which based on the Lithium-ion battery test data published by the National Aeronautics and Space Administration Research Center verify that the proposed framework is an accurate and stable prediction method for the remaining life of Lithium-ion batteries estimation.