Research of MH-Ni Battery State of Charge Estimation Based on Grey System Neural Network Model

Jian Xiong Long

doi:10.4028/www.scientific.net/AMM.66-68.583

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 66-68Research of MH-Ni Battery State of Charge...

Research of MH-Ni Battery State of Charge Estimation Based on Grey System Neural Network Model

Abstract:

In order to effectively achieve MH-Ni battery state of charge estimation, grey system neural network model is put forward to predict battery state of charge by using the parameters of battery pulse current response signal as input for grey system neural network. The state of charge is as the network output and the response parameters of the battery pulse current as the input. The results show that its prediction accuracy of the state of charge can be achieved to requirements of the electric vehicles in applications by this method to predict the state of charge.

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Periodical:

Applied Mechanics and Materials (Volumes 66-68)

Pages:

583-587

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.66-68.583

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Online since:

July 2011

Authors:

Jian Xiong Long

Keywords:

Grey System Neural Network, Inner Resistance, MH/Ni Battery, State of Charge (SOC)

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References

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