电池(电)
指数函数
多项式的
多项式与有理函数建模
锂(药物)
锂离子电池
电池容量
集合预报
计算机科学
回归分析
人工智能
数学
机器学习
数学分析
内分泌学
物理
功率(物理)
医学
量子力学
作者
Yinjiao Xing,W. M. Eden,Kwok‐Leung Tsui,Michael Pecht
标识
DOI:10.1016/j.microrel.2012.12.003
摘要
We developed an ensemble model to characterize the capacity degradation and predict the remaining useful performance (RUP) of lithium-ion batteries. Our model fuses an empirical exponential and a polynomial regression model to track the battery’s degradation trend over its cycle life based on experimental data analysis. Model parameters are adjusted online using a particle filtering (PF) approach. Experiments were conducted to compare our ensemble model’s prediction performance with the individual results of the exponential and polynomial models. A validation set of experimental battery capacity data was used to evaluate our model. In our conclusion, we presented the limitations of our model.
科研通智能强力驱动
Strongly Powered by AbleSci AI