The Remaining Useful Life (RUL) is important for reliability analysis of li-ion battery. Reliability of li-ion battery decreases with shortened the RUL. The RUL of li-ion battery can be revealed by the capacity change. The future change of the capacity is related to the current and the historical states, namely, the capacity change of li-ion battery has Long-Range Dependence (LRD). This article describes a RUL prediction method based on fractional order Lévy stable motion (fLsm), which solves the LRD was not obvious caused by the excessive difference of the integer-order model. First, the LRD of the fLsm is revealed by stability index and integral kernel function with Hurst parameter. Then, the fLsm is used as a diffusion term, which reflects the stochastic and LRD of the RUL degradation, to establish a degradation prediction model. The iterative form of the prediction model is established through the incremental distribution of the fLsm. Finally, the RUL is predicted by the Monte Carlo simulation and degradation prediction model. The predictive performance of the fLsm degradation model is verified by battery data in different operating environments. The reliability of li-ion battery is analyzed by the RUL.
Keywords: Degradation model; Fractional Lévy stable motion; Long-range dependence; Reliability; Remaining useful life.
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