摘要详情

ID / 提交时间

228 / 2025-06-14 23:33:01

标题

Remaining useful life prediction based on nonlinear Wiener process and time-varying correlation model for lithium-ion batteries

关键字

RUL prediction,Copula function,nonlinear Wiener process,MCMC,correlation model

主题及专题

Special Sessions > SSL 10 Reliability of New Energy Storage System

状态

全文待审

作者

Yuhang Li / Beihang University

Cheng Qian / Beihang University

Li Lingyu / Beihang University

Dezhen Yang / Beihang University

Yi Ren / Beihang University

Quan Xia / Beihang University

摘要

Lithium-ion batteries are widely used in a variety of critical applications due to their excellent energy density and low self-discharge rate. Ensuring their reliable operation is essential for both economic performance and operational safety. Among the various tasks in battery health management, accurately predicting the Remaining Useful Life (RUL) of lithium-ion batteries is one of the most critical. However, current RUL prediction methods face significant challenges due to high nonlinearity, data dispersion, and coupled degradation among monitored parameters. To address these issues, this study proposes an RUL prediction method based on a nonlinear Wiener process and time-varying correlation model for lithium-ion batteries. An improved MCMC method is introduced to achieve more accurate parameter estimation of the nonlinear Wiener process. And an adaptive time-varying Copula modeling method is employed to capture the dynamic correlations among degradation parameters. Experimental results demonstrate that the proposed method effectively estimates the nonlinear Wiener process parameters for two key degradation parameters: discharge capacity and internal resistance. Furthermore, modeling their time-varying correlation structure improves the RUL prediction accuracy.