Estimation on State of Charge of Power Battery Based on the Grey Neural Network Model

Lu Lu Du; Bei Li; Huai De Zhang

doi:10.4028/www.scientific.net/AMM.427-429.1158

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429Estimation on State of Charge of Power Battery...

Estimation on State of Charge of Power Battery Based on the Grey Neural Network Model

Abstract:

The state of charge (SOC) of power battery is an important parameter of battery state, and it plays a vital role in real-time accurate estimation, condition monitoring, improving battery life, and ensuring the safety of power supply. This paper presents the grey neural network model of the relation between the battery SOC and rebound voltage, discharge current. Based on this model, a new on-line SOC detection method using rebound voltage and discharge current in the discharge process is proposed. From the testing results, the model and algorithm were proved to be feasible and effective, and the estimated error is controlled within a range of ±8%.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

1158-1162

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.1158

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Online since:

September 2013

Authors:

Lu Lu Du*, Bei Li, Huai De Zhang

Keywords:

Gray Theory, Grey Neural Network, Power Battery, Rebound Voltage, State of Charge (SOC)

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* - Corresponding Author

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