A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur

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dc.contributor.author Fotouhi, Abbas
dc.contributor.author Auger, Daniel J.
dc.contributor.author Propp, Karsten
dc.contributor.author Longo, Stefano
dc.contributor.author Wild, Mark
dc.date.accessioned 2016-07-20T15:10:50Z
dc.date.available 2016-07-20T15:10:50Z
dc.date.issued 2015-12-29
dc.identifier.citation Abbas Fotouhi, Daniel J. Auger, Karsten Propp, Stefano Longo, Mark Wild, A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur, Renewable and Sustainable Energy Reviews, Volume 56, April 2016, pp1008-1021 en_UK
dc.identifier.issn 1364-0321
dc.identifier.issn http://dx.doi.org/10.1016/j.rser.2015.12.009
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/10149
dc.description.abstract Accurate prediction of range of an electric vehicle (EV) is a significant issue and a key market qualifier. EV range forecasting can be made practicable through the application of advanced modelling and estimation techniques. Battery modelling and state-of-charge estimation methods play a vital role in this area. In addition, battery modelling is essential for safe charging/discharging and optimal usage of batteries. Much existing work has been carried out on incumbent Lithium-ion (Li-ion) technologies, but these are reaching their theoretical limits and modern research is also exploring promising next-generation technologies such as Lithium–Sulphur (Li–S). This study reviews and discusses various battery modelling approaches including mathematical models, electrochemical models and electrical equivalent circuit models. After a general survey, the study explores the specific application of battery models in EV battery management systems, where models may have low fidelity to be fast enough to run in real-time applications. Two main categories are considered: reduced-order electrochemical models and equivalent circuit models. The particular challenges associated with Li–S batteries are explored, and it is concluded that the state-of-the-art in battery modelling is not sufficient for this chemistry, and new modelling approaches are needed. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-Non-Commercial-No Derivatives 3.0 (CC BY-NC-ND 3.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
dc.subject Battery modelling en_UK
dc.subject Electric vehicle en_UK
dc.subject Lithium sulphur en_UK
dc.subject Equivalent circuit en_UK
dc.subject Electrochemical en_UK
dc.title A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur en_UK
dc.type Article en_UK


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