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

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dc.contributor.authorFotouhi, Abbas
dc.contributor.authorAuger, Daniel J.
dc.contributor.authorPropp, Karsten
dc.contributor.authorLongo, Stefano
dc.date.accessioned2016-08-12T13:46:27Z
dc.date.available2016-08-12T13:46:27Z
dc.date.issued2016-04-21
dc.description.abstractIn this study, a framework is proposed for battery model identification to be applied in electric vehicle energy storage systems. The main advantage of the proposed approach is having capability to handle different battery chemistries. 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 parametrisation is performed in both cases using the Prediction-Error Minimization (PEM) algorithm applied to experimental data. The use of identified parameters for battery state-of-charge (SOC) estimation is then discussed. It is demonstrated that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery’s open circuit voltage (OCV) is adequate for SOC estimation. However, Li-S battery SOC estimation can be challenging due to the chemistry’s unique features and the SOC cannot be estimated from the OCV-SOC curve alone because of its flat gradient. An observability analysis demonstrates that Li-S battery SOC is not observable using the common state-space representations in the literature. Finally, the problem’s solution is discussed using the proposed framework.en_UK
dc.identifier.citationFotouhi, A. et al. (2016) Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies, Proceedings of the 8th International Conference on Power Electronics, Machines and Drives, 19th - 21st April 2016, Glasgow, UKen_UK
dc.identifier.isbn9781785611889
dc.identifier.urihttp://dx.doi.org/10.1049/cp.2016.0142
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/10296
dc.language.isoenen_UK
dc.publisherIETen_UK
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.titleElectric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studiesen_UK
dc.typeArticleen_UK

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