Remaining useful life prediction for Lithium-ion batteries using fractional Brownian motion and Fruit-fly Optimization Algorithm

In this paper, a novel method base on non-Markovian Fractional Brownian Motion (FBM) is proposed for Lithium-ion batteries remaining useful life (RUL) prediction. Firstly, the FBM degradation model is introduced and the Hurst exponent (H) is calculated. Secondly, the parameters of the FBM model are estimated by maximum likelihood estimation (MLE). The Fruit-fly Optimization Algorithm (FOA) is proposed to optimize the H. Then the procedure for RUL prediction is provided. Capacity degradation data of Lithium-ion batteries is selected as prediction case, and the RUL prediction results are given by two real cases of RUL prediction for lithium-ion batteries. The validity of the proposed method is verified by several evaluation criteria.