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.
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