SOC Estimation on Radial Basis Function

Hui Fang Kong; Liang Jun Xiang; Shun Li Xia

doi:10.4028/www.scientific.net/AMR.403-408.3119

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 403-408SOC Estimation on Radial Basis Function

SOC Estimation on Radial Basis Function

Abstract:

Power lithium battery state of charge (SOC) is an important parameter for the measure of battery charge remaining, SOC estimation of Power lithium battery accurate or not, affect its performance and service life directly. thus, it is particularly important to improving the accuracy estimation of SOC further, combined characteristics of battery time-varying, SOC estimation method was proposed based on radial basis function neural network (RBF) in this paper, experiment results show that the RBF network algorithm can improve the estimation accuracy of SOC.

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Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

3119-3122

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.403-408.3119

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Online since:

November 2011

Authors:

Hui Fang Kong, Liang Jun Xiang, Shun Li Xia

Keywords:

Power Lithium Battery, RBF Network, SOC Estimation, Time-Varying Characteristics

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