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
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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