Multi-Fractal Weibull Adaptive Model for the Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries

In this paper, an adaptive remaining useful life prediction model is proposed for electric vehicle lithium batteries. Capacity degradation of the electric car lithium batteries is modeled by the multi-fractal Weibull motion. The varying degree of long-range dependence and the 1/f characteristics in the frequency domain are also analyzed. The age and state-dependent degradation model is derived, with the associated adaptive drift and diffusion coefficients. The adaptive mechanism considers the quantitative relations between the drift and diffusion coefficients. The unit-to-unit variability is considered a random variable. To facilitate the application, the convergence of the RUL prediction model is proved. Replacement of the lithium battery in the electric car is recommended according to the remaining useful life prediction results. The effectiveness of the proposed model is shown in the case study.

Automated summary

An adaptive remaining useful life prediction model is proposed in this paper for electric vehicle lithium batteries. The capacity degradation of the batteries is modeled using multi-fractal Weibull motion, while the varying degree of long-range dependence and 1/f characteristics in the frequency domain are analyzed. The derived age and state-dependent degradation model includes adaptive drift and diffusion coefficients, which consider the quantitative relations between them. The unit-to-unit variability is considered a random variable, and the convergence of the RUL prediction model is proven for practical application. The model is shown to be effective in a case study.