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Quantitative Analysis of Lithium-Ion Battery Capacity Prediction via Adaptive Bathtub-Shaped Function

Chen, Yi, Miao, Qiang, Zheng, Bin, Wu, Shaomin, Pecht, Michael (2013) Quantitative Analysis of Lithium-Ion Battery Capacity Prediction via Adaptive Bathtub-Shaped Function. Energies, 6 (6). pp. 3082-3096. ISSN 1996-1073. (doi:10.3390/en6063082) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.3390/en6063082

Abstract

Batteries are one of the most important components in many mechatronics systems, as they supply power to the systems and their failures may lead to reduced performance or even catastrophic results. Therefore, the prediction analysis of remaining useful life (RUL) of batteries is very important. This paper develops a quantitative approach for battery RUL prediction using an adaptive bathtub-shaped function (ABF). ABF has been utilised to model the normalised battery cycle capacity prognostic curves, which attempt to predict the remaining battery capacity with given historical test data. An artificial fish swarm algorithm method with a variable population size (AFSAVP) is employed as the optimiser for the parameter determination of the ABF curves, in which the fitness function is defined in the form of a coefficient of determination (R2). A 4 x 2 cross-validation (CV) has been devised, and the results show that the method can work valuably for battery health management and battery life prediction.

Item Type: Article
DOI/Identification number: 10.3390/en6063082
Uncontrolled keywords: remaining useful life; battery capacity; lithium-ion batteries; adaptive bathtub-shaped function; mean average precision; mean standard deviation; swarm fish algorithm
Subjects: H Social Sciences
H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Shaomin Wu
Date Deposited: 09 Sep 2013 11:59 UTC
Last Modified: 29 May 2019 11:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/35145 (The current URI for this page, for reference purposes)
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