Plug-in electric vehicle batteries degradation modeling for smart grid studies: Review, assessment and conceptual framework. (January 2018)

• Record Type: Journal Article
• Authors: Ahmadian, Ali; Sedghi, Mahdi; Elkamel, Ali; Fowler, Michael; Aliakbar Golkar, Masoud
• Is Part Of: Renewable & sustainable energy reviews. Volume 81:Part 2(2018)
• Page Start: 2609
• Page End: 2624
• Publication Date: 2018-01
• Subjects: Plug-in electric vehicles -- Smart grid -- Lithium-ion battery -- V2G -- G2V -- Battery degradation modeling; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2017.06.067
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: The battery is a key component in Plug-in Electric Vehicles (PEVs) whose degradation should be considered in vehicle modeling and if the battery pack is to be used in a Vehicle to Grid (V2G) smart grid studies. Several researchers have proposed different methodologies for PEV batteries degradation modeling from various aspects. Most of the battery degradation literature consists of empirical-based studies with results extracted from experimental tests in laboratories. As such, the results have been presented in non-formulated forms and are of less effectiveness for smart grid researchers. Furthermore, the impact of battery degradation in V2G smart grid have not been examined in smart grid studies. This paper reviews and compares different battery technologies focusing on Lithium-ion batteries which dominant in today and future vehicle applications. After that the most prominent degradation models are assessed, the effects of degradation factors on battery performance are examined. The literature shows that the degradation causes can be categorized into two groups namely calendar ageing and cycling ageing. Generally, the calendar ageing is influenced by temperature, time, and state of charge, while the cycling ageing is influenced by cycle number, charge rate and depth of discharge. Finally, in this work a conceptual framework for battery degradation modeling is proposed that can be easily used in smart grid studies, without necessarily requiring a detailed understanding of fundamental electrochemical processes. The proposed framework considers not only the battery degradation modeling, but also that of other related components in a smart grid.