Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies

Show simple item record

dc.contributor.author Fotouhi, Abbas
dc.contributor.author Auger, Daniel
dc.contributor.author Propp, Karsten
dc.contributor.author Longo, Stefano
dc.date.accessioned 2017-07-24T11:01:50Z
dc.date.available 2017-07-24T11:01:50Z
dc.date.issued 2017-07-06
dc.identifier.citation Fotouhi A, Auger DJ, Propp K, Longo S. (2017) Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies. IET Power Electronics, Volume 10, Issue 11, 2017, pp. 1289-1297 en_UK
dc.identifier.issn 1755-4535
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/12228
dc.description.abstract In this study, battery model identification is performed to be applied in electric vehicle battery management systems. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and lithium-sulphur (Li-S), a promising next-generation technology. Equivalent circuit battery model parameterisation is performed in both cases using the prediction-error minimisation algorithm applied to experimental data. Performance of a Li-S cell is also tested based on urban dynamometer driving schedule (UDDS) and the proposed parameter identification framework is applied in this case as well. The identification results are then validated against the exact values of the battery parameters. The use of identified parameters for battery state-of-charge (SOC) estimation is also discussed. It is shown that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereas Li-S battery SOC estimation is more challenging due to its unique features such as flat OCV–SOC curve. An observability analysis shows that Li-S battery SOC is not fully observable and the existing methods in the literature might not be applicable for a Li-S cell. Finally, the effect of temperature on the identification results and the observability is discussed by repeating the UDDS test at 5, 10, 20, 30, 40 and 50°C. en_UK
dc.language.iso en en_UK
dc.publisher The Institution of Engineering and Technology en_UK
dc.rights Attribution 3.0 International
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.title Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies en_UK
dc.type Article en_UK


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution 3.0 International Except where otherwise noted, this item's license is described as Attribution 3.0 International

Search CERES


Browse

My Account

Statistics