电力系统保护与控制2024，Vol.52Issue(9)：123-131,9.DOI:10.19783/j.cnki.pspc.231034
基于改进粒子滤波的锂离子电池剩余寿命预测
Improved particle filter algorithm for remaining useful life prediction of lithium-ion batteries
摘要
Abstract
A prediction method based on improved particle filtering is proposed to improve the low accuracy and poor generalizability of the remaining life prediction of lithium-ion batteries.First,a double Gaussian model is taken as a degradation empirical model to fit the capacity degradation process of lithium-ion batteries.Then the initial parameters of the degradation model are set by using a priori knowledge,and the particle filtering method is used to update the parameters.The Gaussian mixture method for particle resampling is proposed to solve the particle degradation problem.This fits the complex nonlinear distribution and long-tailed distribution of particles in the resampling process,and ensures that the probability density distribution status of the prediction results is uniform and concentrated.Finally,experimental validation is carried out on different datasets,and the results show that the improved particle filtering method proposed has high accuracy and strong robustness.关键词
锂离子电池/剩余寿命预测/粒子滤波/高斯混合模型Key words
Li-ion battery/remaining useful life/particle filter/Gaussian mixture model引用本文复制引用
刘博,尹杰,李然..基于改进粒子滤波的锂离子电池剩余寿命预测[J].电力系统保护与控制,2024,52(9):123-131,9.基金项目
This work is supported by the Natural Science Foundation of Heilongjiang Province(No.LH2022E088). 黑龙江省自然科学基金项目资助(LH2022E088) （No.LH2022E088）
教育部联合发展基金项目资助(8091B022133) （8091B022133）
