Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries
Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-01-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/10/1/90 |
| _version_ | 1798042495213371392 |
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| author | Thomas R. B. Grandjean Andrew McGordon Paul A. Jennings |
| author_facet | Thomas R. B. Grandjean Andrew McGordon Paul A. Jennings |
| author_sort | Thomas R. B. Grandjean |
| collection | DOAJ |
| description | Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite of the modelling process, especially when the parameters represent physical battery attributes and the proposed model is utilised to estimate them. Numerical estimates for unidentifiable parameters are effectively meaningless since unidentifiable parameters have an infinite number of possible numerical solutions. It is demonstrated that the physical phenomena assignment to a two-RC (resistor–capacitor) network equivalent circuit model (ECM) is not possible without additional information. Established methods to ascertain structural identifiability are applied to 12 ECMs covering the majority of model templates used previously. Seven ECMs are shown not to be uniquely identifiable, reducing the confidence in the accuracy of the parameter values obtained and highlighting the relevance of structural identifiability even for relatively simple models. Suggestions are proposed to make the models identifiable and, therefore, more valuable in battery management system applications. The detailed analyses illustrate the importance of structural identifiability prior to performing parameter estimation experiments, and the algebraic complications encountered even for simple models. |
| first_indexed | 2024-04-11T22:36:18Z |
| format | Article |
| id | doaj.art-f327eab557d74a02878783847075ec75 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T22:36:18Z |
| publishDate | 2017-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f327eab557d74a02878783847075ec752022-12-22T03:59:13ZengMDPI AGEnergies1996-10732017-01-011019010.3390/en10010090en10010090Structural Identifiability of Equivalent Circuit Models for Li-Ion BatteriesThomas R. B. Grandjean0Andrew McGordon1Paul A. Jennings2Energy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UKEnergy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UKEnergy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UKStructural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite of the modelling process, especially when the parameters represent physical battery attributes and the proposed model is utilised to estimate them. Numerical estimates for unidentifiable parameters are effectively meaningless since unidentifiable parameters have an infinite number of possible numerical solutions. It is demonstrated that the physical phenomena assignment to a two-RC (resistor–capacitor) network equivalent circuit model (ECM) is not possible without additional information. Established methods to ascertain structural identifiability are applied to 12 ECMs covering the majority of model templates used previously. Seven ECMs are shown not to be uniquely identifiable, reducing the confidence in the accuracy of the parameter values obtained and highlighting the relevance of structural identifiability even for relatively simple models. Suggestions are proposed to make the models identifiable and, therefore, more valuable in battery management system applications. The detailed analyses illustrate the importance of structural identifiability prior to performing parameter estimation experiments, and the algebraic complications encountered even for simple models.http://www.mdpi.com/1996-1073/10/1/90structural identifiabilitylithium ion battery modellingequivalent circuit models |
| spellingShingle | Thomas R. B. Grandjean Andrew McGordon Paul A. Jennings Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries Energies structural identifiability lithium ion battery modelling equivalent circuit models |
| title | Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries |
| title_full | Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries |
| title_fullStr | Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries |
| title_full_unstemmed | Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries |
| title_short | Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries |
| title_sort | structural identifiability of equivalent circuit models for li ion batteries |
| topic | structural identifiability lithium ion battery modelling equivalent circuit models |
| url | http://www.mdpi.com/1996-1073/10/1/90 |
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