期刊
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 56, 期 -, 页码 1008-1021出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2015.12.009
关键词
Battery modelling; Electric vehicle; Lithium sulphur; Equivalent circuit; Electrochemical
资金
- Revolutionary Electronic Battery (REVB) [TS/L000903/1]
- Innovate UK
- Future Vehicle Project - EPSRC [EP/I038586/1]
- Cranfield University's Impact Acceleration Account - EPSRC [EP/K503927/1]
- EPSRC [EP/I038586/1, EP/L505286/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K503927/1, EP/L505286/1, EP/I038586/1] Funding Source: researchfish
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. (C) 2015 Elsevier Ltd. All rights reserved.
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