Structural Identifiability of a Pseudo-2D Li-ion Battery Electrochemical Model⁎Work supported by the Engineering and Physical Sciences Research Council through grant EP/P005411/1- "Structured electrodes for improved energy storage.". Issue 2 (2020)
- Record Type:
- Journal Article
- Title:
- Structural Identifiability of a Pseudo-2D Li-ion Battery Electrochemical Model⁎Work supported by the Engineering and Physical Sciences Research Council through grant EP/P005411/1- "Structured electrodes for improved energy storage.". Issue 2 (2020)
- Main Title:
- Structural Identifiability of a Pseudo-2D Li-ion Battery Electrochemical Model⁎Work supported by the Engineering and Physical Sciences Research Council through grant EP/P005411/1- "Structured electrodes for improved energy storage."
- Authors:
- Drummond, Ross
Duncan, Stephen R. - Abstract:
- Abstract: Growing demand for fast charging and optimised battery designs is fuelling significant interest in electrochemical models of Li-ion batteries. However, estimating parameter values for these models remains a major challenge. In this paper, a structural identifiability analysis was applied to a pseudo-2D Li-ion electrochemical battery model that can be considered as a linearised and decoupled form of the benchmark Doyle-Fuller-Newman model. From an inspection of the impedance function, it was shown that this model is uniquely parametrised by 21 parameters, being combinations of the electrochemical parameters like the conductivities and diffusion coefficients. The well-posedness of the parameter estimation problem with these parameters was then established. This result could lead to more realistic predictions about the internal state of the battery by identifying the parameter set that can be uniquely identified from the data.
- Is Part Of:
- IFAC-PapersOnLine. Volume 53:Issue 2(2020)
- Journal:
- IFAC-PapersOnLine
- Issue:
- Volume 53:Issue 2(2020)
- Issue Display:
- Volume 53, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 53
- Issue:
- 2
- Issue Sort Value:
- 2020-0053-0002-0000
- Page Start:
- 12452
- Page End:
- 12458
- Publication Date:
- 2020
- Subjects:
- Li-ion batteries -- electrochemical models -- structural identifiability
Automatic control -- Periodicals
629.805 - Journal URLs:
- https://www.journals.elsevier.com/ifac-papersonline/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.ifacol.2020.12.1328 ↗
- Languages:
- English
- ISSNs:
- 2405-8963
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23657.xml