A model for state-of-health estimation of lithium ion batteries based on charging profiles

Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the state-of-health of lithium ion batteries. The model is an incremental capacity analysis-based model, which applies a capacity model to define the depend...

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Published inEnergy (Oxford) Vol. 177; pp. 57 - 65
Main Authors Bian, Xiaolei, Liu, Longcheng, Yan, Jinying
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 15.06.2019
Elsevier BV
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Abstract Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the state-of-health of lithium ion batteries. The model is an incremental capacity analysis-based model, which applies a capacity model to define the dependence of the state of charge on the open circuit voltage as the battery ages. It can be learning-free, with the parameters subject to certain constraints, and is able to give efficient and reliable estimates of the state-of-health for various lithium ion batteries at any aging status. When applied to a fresh LiFePO4 cell, the state-of-health estimated by this model (learning-unrequired or learning-required) shows a close correspondence to the available measured data, with an absolute difference of 0.31% or 0.12% at most, even for significant temperature fluctuation. In addition, NASA battery datasets are employed to demonstrate the versatility and applicability of the model to different chemistries and cell designs. •An ICA-based model is proposed to estimate SOH of LIBs.•The ICA-based model can be learning-required or learning-unrequired.•This model can give reliable estimates of SOH for various LIBs at any aging status.•The accuracy of the model is validated by experimental results of LFP and NCA batteries.
AbstractList Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the state-of-health of lithium ion batteries. The model is an incremental capacity analysis-based model, which applies a capacity model to define the dependence of the state of charge on the open circuit voltage as the battery ages. It can be learning-free, with the parameters subject to certain constraints, and is able to give efficient and reliable estimates of the state-of-health for various lithium ion batteries at any aging status. When applied to a fresh LiFePO4 cell, the state-of-health estimated by this model (learning-unrequired or learning-required) shows a close correspondence to the available measured data, with an absolute difference of 0.31% or 0.12% at most, even for significant temperature fluctuation. In addition, NASA battery datasets are employed to demonstrate the versatility and applicability of the model to different chemistries and cell designs.
Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the state-of-health of lithium ion batteries. The model is an incremental capacity analysis-based model, which applies a capacity model to define the dependence of the state of charge on the open circuit voltage as the battery ages. It can be learning-free, with the parameters subject to certain constraints, and is able to give efficient and reliable estimates of the state-of-health for various lithium ion batteries at any aging status. When applied to a fresh LiFePO 4 cell, the state-of-health estimated by this model (learning-unrequired or learning-required)shows a close correspondence to the available measured data, with an absolute difference of 0.31% or 0.12% at most, even for significant temperature fluctuation. In addition, NASA battery datasets are employed to demonstrate the versatility and applicability of the model to different chemistries and cell designs.
Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the state-of-health of lithium ion batteries. The model is an incremental capacity analysis-based model, which applies a capacity model to define the dependence of the state of charge on the open circuit voltage as the battery ages. It can be learning-free, with the parameters subject to certain constraints, and is able to give efficient and reliable estimates of the state-of-health for various lithium ion batteries at any aging status. When applied to a fresh LiFePO4 cell, the state-of-health estimated by this model (learning-unrequired or learning-required) shows a close correspondence to the available measured data, with an absolute difference of 0.31% or 0.12% at most, even for significant temperature fluctuation. In addition, NASA battery datasets are employed to demonstrate the versatility and applicability of the model to different chemistries and cell designs. •An ICA-based model is proposed to estimate SOH of LIBs.•The ICA-based model can be learning-required or learning-unrequired.•This model can give reliable estimates of SOH for various LIBs at any aging status.•The accuracy of the model is validated by experimental results of LFP and NCA batteries.
Author Yan, Jinying
Bian, Xiaolei
Liu, Longcheng
Author_xml – sequence: 1
  givenname: Xiaolei
  surname: Bian
  fullname: Bian, Xiaolei
  email: xiaoleib@kth.se
  organization: Department of Chemical Engineering, KTH-Royal Institute of Technology, 100 44 Stockholm, Sweden
– sequence: 2
  givenname: Longcheng
  surname: Liu
  fullname: Liu, Longcheng
  organization: Department of Chemical Engineering, KTH-Royal Institute of Technology, 100 44 Stockholm, Sweden
– sequence: 3
  givenname: Jinying
  surname: Yan
  fullname: Yan, Jinying
  organization: Department of Chemical Engineering, KTH-Royal Institute of Technology, 100 44 Stockholm, Sweden
BackLink https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252451$$DView record from Swedish Publication Index
https://research.chalmers.se/publication/534539$$DView record from Swedish Publication Index
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Keywords Incremental capacity analysis
Lithium ion battery
Equivalent circuit model
State of health
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Snippet Using an equivalent circuit model to characterize the constant-current part of a charging/discharging profile, a model is developed to estimate the...
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SubjectTerms Aging
Charging
Circuits
data collection
Dependence
electric potential difference
Equivalent circuit model
Equivalent circuits
Health
Incremental capacity analysis
Learning
Lithium
lithium batteries
Lithium ion battery
Lithium-ion batteries
Open circuit voltage
Organic chemistry
Product design
Rechargeable batteries
State of health
temperature
Variation
Title A model for state-of-health estimation of lithium ion batteries based on charging profiles
URI https://dx.doi.org/10.1016/j.energy.2019.04.070
https://www.proquest.com/docview/2246255030
https://www.proquest.com/docview/2237508303
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https://research.chalmers.se/publication/534539
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