Accuracy versus simplicity in online battery model identification

dc.contributor.authorFotouhi, Abbas
dc.contributor.authorAuger, Daniel J.
dc.contributor.authorPropp, Karsten
dc.contributor.authorLongo, Stefano
dc.date.accessioned2016-11-02T15:38:57Z
dc.date.available2016-11-02T15:38:57Z
dc.date.issued2016-09-22
dc.description.abstractThis paper presents a framework for battery modeling in online, real-time applications where accuracy is important but speed is the key. The framework allows users to select model structures with the smallest number of parameters that is consistent with the accuracy requirements of the target application. The tradeoff between accuracy and speed in a battery model identification process is explored using different model structures and parameter-fitting algorithms. Pareto optimal sets are obtained, allowing a designer to select an appropriate compromise between accuracy and speed. In order to get a clearer understanding of the battery model identification problem, “identification surfaces” are presented. As an outcome of the battery identification surfaces, a new analytical solution is derived for battery model identification using a closed-form formula to obtain a battery’s ohmic resistance and open circuit voltage from measurement data. This analytical solution is used as a benchmark for comparison of other fitting algorithms and it is also used in its own right in a practical scenario for state-of-charge estimation. A simulation study is performed to demonstrate the effectiveness of the proposed framework and the simulation results are verified by conducting experimental tests on a small NiMH battery pack.en_UK
dc.identifier.citationFotouhi A, Auger DJ, Propp K, Longo S. (2016) Accuracy versus simplicity in online battery model identification. IEEE Transactions on Systems Man and Cybernetics: Systems, Volume 48, Issue 2, 2016, pp.195-206en_UK
dc.identifier.grantnumberEP/L505286/1
dc.identifier.issn2168-2216
dc.identifier.urihttps//doi.org/10.1109/TSMC.2016.2599281
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/10923
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.subjectBatteryen_UK
dc.subjectelectric vehicle (EV)en_UK
dc.subjectequivalent circuit modellingen_UK
dc.subjectidentificationen_UK
dc.subjectoptimizationen_UK
dc.titleAccuracy versus simplicity in online battery model identificationen_UK
dc.typeArticleen_UK

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