Gaussian process regression-based modelling of lithium-ion battery temperature-dependent open-circuit-voltage

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

9 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)1214-1216
Journal / PublicationElectronics Letters
Volume53
Issue number17
Online published24 Jul 2017
Publication statusPublished - 17 Aug 2017

Abstract

Open-circuit-voltage (OCV) plays a significant role in state-of-charge (SOC) estimation for lithium-ion batteries. The slight difference in OCV at various temperatures can result in a large deviation of SOC estimation. In this Letter, a novel model based on Gaussian process regression is proposed to describe the sophisticated relationship among the OCV, SOC, and temperature. To validate the effectiveness of the proposed model, a comprehensive comparison with widely considered benchmarking OCV models is conducted. Experiment results demonstrate the proposed model can provide the most accurate prediction of OCV compared with benchmarking models.