Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation

Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation

Effective prognosis of lithium-ion batteries involves the inclusion of the influences of uncertainties that can be incorporated through random effect parameters in a nonlinear mixed effect degradation model framework. This study is geared towards the estimation of the reliability of lithium-ion batt...

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Bibliographic Details
Main Authors: Chinedu I. Ossai, Nagarajan Raghavan
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Batteries
Subjects:
charge capacity decay
end of life
reliability
state of health
uncertainty
Weibull distribution function
Online Access:https://www.mdpi.com/2313-0105/3/4/32
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spelling doaj-81fc48568b9d4b1b8ca3a62e61cd124c2020-11-24T20:42:45ZengMDPI AGBatteries2313-01052017-10-01343210.3390/batteries3040032batteries3040032Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay EstimationChinedu I. Ossai0Nagarajan Raghavan1Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore 487372, SingaporeEngineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore 487372, SingaporeEffective prognosis of lithium-ion batteries involves the inclusion of the influences of uncertainties that can be incorporated through random effect parameters in a nonlinear mixed effect degradation model framework. This study is geared towards the estimation of the reliability of lithium-ion batteries, using parametric effects determination involving uncertainty, using a multiphase decay patterned sigmoidal model, experimental data and the Weibull distribution function. The random effect model, which uses Maximum Likelihood Estimation (MLE) and Stochastic Approximation Expectation Maximization (SAEM) algorithm to predict the parametric values, was found to estimate the remaining useful life (RUL) to an accuracy of more than 98%. The State-of-Health (SOH) of the batteries was estimated using the Weibull distribution function, which is found to be an appropriate formulation to use.https://www.mdpi.com/2313-0105/3/4/32charge capacity decayend of lifereliabilitystate of healthuncertaintyWeibull distribution function
collection DOAJ
language English
format Article
sources DOAJ
author Chinedu I. Ossai
Nagarajan Raghavan
spellingShingle Chinedu I. Ossai
Nagarajan Raghavan
Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
Batteries
charge capacity decay
end of life
reliability
state of health
uncertainty
Weibull distribution function
author_facet Chinedu I. Ossai
Nagarajan Raghavan
author_sort Chinedu I. Ossai
title Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
title_short Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
title_full Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
title_fullStr Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
title_full_unstemmed Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation
title_sort statistical characterization of the state-of-health of lithium-ion batteries with weibull distribution function—a consideration of random effect model in charge capacity decay estimation
publisher MDPI AG
series Batteries
issn 2313-0105
publishDate 2017-10-01
description Effective prognosis of lithium-ion batteries involves the inclusion of the influences of uncertainties that can be incorporated through random effect parameters in a nonlinear mixed effect degradation model framework. This study is geared towards the estimation of the reliability of lithium-ion batteries, using parametric effects determination involving uncertainty, using a multiphase decay patterned sigmoidal model, experimental data and the Weibull distribution function. The random effect model, which uses Maximum Likelihood Estimation (MLE) and Stochastic Approximation Expectation Maximization (SAEM) algorithm to predict the parametric values, was found to estimate the remaining useful life (RUL) to an accuracy of more than 98%. The State-of-Health (SOH) of the batteries was estimated using the Weibull distribution function, which is found to be an appropriate formulation to use.
topic charge capacity decay
end of life
reliability
state of health
uncertainty
Weibull distribution function
url https://www.mdpi.com/2313-0105/3/4/32
work_keys_str_mv AT chineduiossai statisticalcharacterizationofthestateofhealthoflithiumionbatterieswithweibulldistributionfunctionaconsiderationofrandomeffectmodelinchargecapacitydecayestimation
AT nagarajanraghavan statisticalcharacterizationofthestateofhealthoflithiumionbatterieswithweibulldistributionfunctionaconsiderationofrandomeffectmodelinchargecapacitydecayestimation
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