Application Research of WNN Optimized by GA in VRLA Battary Degradation Prediction

Suai Feng Wang; Chang Li; Xiao Qing Xie; Jun Wang

doi:10.4028/www.scientific.net/AMM.644-650.2087

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Application Research of WNN Optimized by GA in...

Application Research of WNN Optimized by GA in VRLA Battary Degradation Prediction

Abstract:

This paper studies the accurate prediction problem of VRLA battery state of charge (SOC) and the remaining capability of the battery, after the comprehensive analysis of the various elements which affect the battery state of charge, we put forward a battery degradation test model based on GA - WNN, and carries on the verification test, in the meantime, we also make it contrast with other algorithms. The results of test show that the model of WNN Optimized by GA has shorter training time and high prediction accuracy, it can predict the battery remaining power more accurately.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

2087-2091

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.2087

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Cite this paper

Online since:

September 2014

Authors:

Suai Feng Wang*, Chang Li, Xiao Qing Xie, Jun Wang

Keywords:

Genetic Algorithm (GA), SOH, VRLA Battery, Wavelet Neural Network

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* - Corresponding Author

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