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

  • Yinjiao Xing
  • , Eden W.M. Ma
  • , Kwok-Leung Tsui
  • , Michael Pecht

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    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. © 2013 Elsevier Ltd. All rights reserved.
    Original languageEnglish
    Pages (from-to)811-820
    JournalMicroelectronics Reliability
    Volume53
    Issue number6
    Online published11 Jan 2013
    DOIs
    Publication statusPublished - Jun 2013

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Policy Impact

    • Cited in Policy Documents

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