Accelerated Stress Factors Based Nonlinear Wiener Process Model for Lithium-Ion Battery Prognostics

Accurate remaining useful life (RUL) of batteries plays an imperative role in ensuring safe operations and avoiding catastrophic accidents. However, in practice, complicated working conditions bring challenges to accurate battery prognostics. In this article, an accelerated stress factors-based nonlinear Wiener process model is proposed to enrich inadequate battery prognostic works at various operating conditions. To realize online individual battery prognostics, once a new measurement is available, the parameters of a state-space model constructed by the proposed model are posteriorly updated. Then, based on the Peukert law and the Arrhenius equation, two specific accelerated stress-relevant drift functions and their associated degradation models at different discharge rates and temperatures are respectively designed. Subsequently, RUL predictions are conducted using the proposed method. RUL predictions at different discharge rates and different temperatures demonstrate the accuracy and robustness of the proposed prognostic models. According to some general prognostic metrics, the proposed method is proved to be superior to four existing RUL prediction approaches.

Automated summary

In this article, an accelerated stress factors-based nonlinear Wiener process model is proposed to improve battery prognostics under different working conditions. The method enables online individual battery prognostics by updating model parameters and designing accelerated stress-relevant drift functions. RUL predictions are conducted at different discharge rates and temperatures to demonstrate the accuracy and robustness of the proposed method.