Data‐driven battery degradation model leveraging average degradation function fitting. Issue 2 (1st January 2017)

• Record Type: Journal Article
• Authors: Kim, K.; Choi, Y.; Kim, H.
• Is Part Of: Electronics letters. Volume 53:Issue 2(2017)
• Page Start: 102
• Page End: 104
• Publication Date: 2017-01-01
• Subjects: battery powered vehicles -- power grids -- curve fitting; data‐driven battery degradation model -- average degradation function fitting -- electrical vehicles -- vehicle‐to‐grid ancillary service -- battery life -- battery usage -- cycle life‐based approach -- degradation density function -- curve fitting -- V2G ancillary service -- DDF; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2016.3096
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : When the batteries of electrical vehicles are used to provide vehicle‐to‐grid (V2G) ancillary service, battery life is shortened due to additional battery usage. To consider battery degradation, cycle life‐based approach with degradation density function (DDF) is popular. However, the previous modelling cannot capture the well‐known fact that battery may severely degrade at both ends of battery, i.e. when full or empty. A novel method of obtaining DDF using the curve fitting over average degradation function is proposed. The proposed method tightly fits the empirical measurements and thus provides a better way of operating V2G considering battery degradation. The results show that the proposed method reduces battery degradation by up to 28.9% while achieving the same revenue.