Predicting the lifetimes of LiFePO4 batteries on the basis of the gamma process through accelerated degradation measurements

Yu Chang Lin, Kuan Jung Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This study mainly focused on evaluating the capacity fade of LiFePO4 batteries by using a novel dual dynamic stress accelerated degradation test, called D2SADT. This test method was developed to simulate a situation involving driving an electric vehicle in the city. D2SADT contains two controllable dynamic stress variables: the environmental factor corresponding to temperature cycling and the power factor corresponding to charging-discharging currents and times at which they were implemented simultaneously. A reference power test was performed repeatedly at a certain time (e.g., five temperature cycles), and the cell capacity was then calculated to monitor the degradation of the batteries. A compositional reliability assessment using the gamma process and Monte Carlo simulation was implemented to calculate the likelihood values of the test samples, LiFePO4 batteries, on the basis of their capacity loss. The test results indicate that the battery capacity decreases over time, validating the novel test method (D2SADT). Moreover, the modeling results indicate that the gamma process combined with Monte Carlo simulation provide superior accuracy for predicting the lifetimes of the test batteries compared with the baseline lifetime data (true degradation route and lifetime). Furthermore, the results indicate the high prediction performance of the proposed model because an error rate of within 5% was obtained after half of the cycles were completed (70 temperature cycles), including the measurements.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509003822
DOIs
Publication statusPublished - 2016 Aug 12
Event2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 - Ottawa, Canada
Duration: 2016 Jun 202016 Jun 22

Other

Other2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
CountryCanada
CityOttawa
Period16-06-2016-06-22

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All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

Cite this

Lin, Y. C., & Chung, K. J. (2016). Predicting the lifetimes of LiFePO4 batteries on the basis of the gamma process through accelerated degradation measurements. In 2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 [7542849] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPHM.2016.7542849