Open AccessData‐driven battery degradation model leveraging average degradation function fitting
Author(s) -
Kim K.,
Choi Y.,
Kim H.
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2016.3096
Subject(s) - degradation (telecommunications) , battery (electricity) , battery capacity , computer science , function (biology) , reliability engineering , automotive engineering , charge cycle , engineering , automotive battery , power (physics) , telecommunications , physics , quantum mechanics , evolutionary biology , biology
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.