A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur. (April 2016)

• Record Type: Journal Article
• Authors: Fotouhi, Abbas; Auger, Daniel J.; Propp, Karsten; Longo, Stefano; Wild, Mark
• Is Part Of: Renewable & sustainable energy reviews. Volume 56(2016:Apr.)
• Page Start: 1008
• Page End: 1021
• Publication Date: 2016-04
• Subjects: Battery modelling -- Electric vehicle -- Lithium sulphur -- Equivalent circuit -- Electrochemical; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2015.12.009
• Languages: English
• ISSNs: 1364-0321

Abstract

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.