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Comparison of lumped diffusion models for voltage prediction of a lithium-ion battery cell during dynamic loads
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.ORCID iD: 0000-0001-9203-9313
2018 (English)In: Journal of Power Sources, ISSN 0378-7753, E-ISSN 1873-2755, Vol. 402, p. 296-300Article in journal (Refereed) Published
Abstract [en]

Three different time-dependent lumped battery models are presented, using a limited set of only either three or four fitting parameters. The models all include one linear (resistive), one non-linear (kinetic) and one time-dependent element, the latter describing the diffusive processes in the battery. The voltage predictive capabilities of the models versus experimental dynamic load data for a plug-in hybrid vehicle battery are compared. It is shown that models based on a diffusion equation in an idealized particle perform similarly to a model based on an RC (resistive-capacitor) pair. In addition, by exchanging the RC element by a diffusion equation in an idealized particle it is also shown that it is possible to reduce the number of needed fitting parameters by one. 

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 402, p. 296-300
Keywords [en]
Battery management systems, Diffusion, Dynamic loads, Partial differential equations, Plug-in hybrid vehicles, Diffusion equations, Diffusion model, Diffusive process, Experimental dynamics, Fitting parameters, Model-based OPC, Predictive capabilities, Voltage prediction, Lithium-ion batteries
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-236624DOI: 10.1016/j.jpowsour.2018.09.020ISI: 000449447800035Scopus ID: 2-s2.0-85053505550OAI: oai:DiVA.org:kth-236624DiVA, id: diva2:1263098
Note

QC 20181126

Available from: 2018-11-14 Created: 2018-11-14 Last updated: 2018-11-26Bibliographically approved

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Lindbergh, Göran

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CiteExportLink to record
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