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Grey system theory-based capacity estimation method for Li-ion batteries

Lookup NU author(s): Dr Li Chen, Dr Bing Ji


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The SOC and SoH of Li-ion batteries are of prime importance in EVs and their condition monitoring techniques have been extensively studied. This paper proposes a grey system theory for predicting the battery capacity and healthy conditions in relation to their discharge cycles. Numerical results via grey system theory-based models are obtained based on the aging data from NASA prognostics data repository. Therefore, the accuracy for the SOC estimation can be examined and improved. In this paper, the accuracy of different grey models including GM (1,1), segmental GM (1,1), Verhulst model, sliding window Verhulst model are investigated and the sliding window Verhulst model is found to be effective for EV batteries.

Publication metadata

Author(s): Chen L, Ji B, Cao WP, Pan HH, Tian BB, Lin WL

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

Year of Conference: 2014

Online publication date: 19/06/2014

Acceptance date: 01/01/1900

Publisher: IET


DOI: 10.1049/cp.2014.0290

Library holdings: Search Newcastle University Library for this item

ISBN: 9781849198158