Liu He, Song Wanqing, Zio Enrico
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, China.
Energy Department, Politecnico di Milano, Via La Masa 34/3, Milano, 20156, Italy; MINES ParisTech, PSL Research University, CRC, Sophia Antipolis, France.
ISA Trans. 2022 Jun;125:360-370. doi: 10.1016/j.isatra.2021.07.002. Epub 2021 Jul 9.
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.
剩余使用寿命（RUL）对于锂离子电池的可靠性分析至关重要。锂离子电池的可靠性会随着RUL的缩短而降低。锂离子电池的RUL可通过容量变化来揭示。容量的未来变化与当前状态和历史状态相关，即锂离子电池的容量变化具有长程相关性（LRD）。本文描述了一种基于分数阶Lévy稳定运动（fLsm）的RUL预测方法，该方法解决了整数阶模型差异过大导致LRD不明显的问题。首先，通过具有赫斯特参数的稳定性指标和积分核函数揭示fLsm的LRD。然后，将fLsm用作反映RUL退化的随机性和LRD的扩散项，建立退化预测模型。通过fLsm的增量分布建立预测模型的迭代形式。最后，通过蒙特卡罗模拟和退化预测模型预测RUL。利用不同运行环境下的电池数据验证了fLsm退化模型的预测性能。通过RUL分析锂离子电池的可靠性。
