An ensemble model for predicting the remaining useful performance of lithium-ion batteries
An ensemble model for predicting the remaining useful performance of lithium-ion batteries
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DOI：
10.1016/j.microrel.2012.12.003
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发表时间：
2013-06-01
影响因子：
1.6
通讯作者：
Pecht, Michael
中科院分区：
文献类型：
--
作者：
Xing, Yinjiao;Ma, Eden W. M.;Pecht, Michael
我们开发了一个集成模型来表征容量退化和预测剩余有用性能（RUP）的锂离子电池。我们的模型融合了经验指数和多项式回归模型，以跟踪电池的退化趋势，在其循环寿命的基础上，实验数据分析。使用粒子滤波（PF）方法在线调整模型参数。实验进行了比较我们的集成模型的预测性能的指数和多项式模型的个人结果。一组验证的实验电池容量数据被用来评估我们的模型。在我们的结论中，我们提出了我们的模型的局限性。(C)2012爱思唯尔有限公司保留所有权利。
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. (C) 2012 Elsevier Ltd. All rights reserved.