Stochastic model for lithium ion battery lifecycle prediction and parametric uncertainties
Date
2018
Authors
Ossai, C.I.
Raghavan, N.
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Conference paper
Citation
2018 Annual Reliability and Maintainability Symposium (RAMS), 2018, iss.8463112, pp.1-6
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64th Annual Reliability & Maintainability Symposium; RAMS 2018 (22 Jan 2018 - 25 Jan 2018 : Nevada, US)
Abstract
Lithium ion batteries plays a vital role in the technological sphere as an enabler for operation of many mobile devices due to their ability to hold charge for a considerably long period. Despite the proliferation of lithium ion batteries, research is still needed to assess and quantify the effects of model parameters on the charge capacity decay and the techniques for estimating the state of health of the batteries. This study uses a stochastic modeling technique that is based on the multiphase decay rate sigmoidal model, to study the battery charge capacity decay over time and determine the effects of the charge decay model parameters on the decay pattern of the batteries. The variabilities of the state of charge (SoC) of the batteries over the lifecycle phases were also studied using the Weibull distribution function and the reliability was estimated for 70% and 60% end-of-life (EOL) failure thresholds.
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Copyright 2017 IEEE