Microelectronics Reliability, Volume 53, Issue 6, Pages 811–820, June 2013

An ensemble model for predicting the remaining useful performance of lithium-ion batteries

Yinjiao Xing a,b,*, Eden W.M. Ma a, Kwok-Leung Tsui a,b, Michael Pecht c
a Centre for Prognostics and System Health Management, City University of Hong Kong, Kowloon, Hong Kong
b Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong
c Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20740, USA

Abstract:

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.

Complete article is available from the publisher and to the CALCE Consortium Members.



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