A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur

Abbas Fotouhi, Daniel J. Auger, Karsten Propp, Stefano Longo and Mark Wild

Renewable and Sustainable Energy Reviews, 2016, vol. 56, issue C, 1008-1021

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.

Keywords: Battery modelling; Electric vehicle; Lithium sulphur; Equivalent circuit; Electrochemical (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (61)

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DOI: 10.1016/j.rser.2015.12.009

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