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SOC Prediction Method of a New Lithium Battery Based on GA-BP Neural Network

  • Kai GuanEmail author
  • Zhiqiang Wei
  • Bo Yin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 355)

Abstract

The prediction of a battery’s state of charge (SOC) is one of the key tasks of battery management. Lithium battery internal chemical reactions are complex and have many factors; its SOC prediction has strong nonlinear characteristics. This paper discussed a SOC prediction model which is based on hybrid genetic algorithm and BP neural network. Set BP neural network’s training error as genetic algorithm fitness value, and then iterate to find the optimal individual as the neural network initialization thresholds and weights. Simulation results show that this method can accurately predict the new kind of a lithium battery’s SOC and have higher accuracy compared with BP neural network.

Keywords

State of charge Genetic algorithm BP neural networks Prediction method 

Notes

Acknowledgments

This work was financially supported by National 863 Plan Project (2014AA052303-5).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.College of Information Science and EngineeringOcean University of ChinaQingdaoChina

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