Classification of Capacity Loss Degree of Vanadium Redox Flow Battery Based on Probabilistic Neural Network

Hong Fei Cao; Xin Jian Zhu; Hai Feng Shen; Meng Shao

doi:10.4028/www.scientific.net/AMM.448-453.2872

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 448-453Classification of Capacity Loss Degree of Vanadium...

Classification of Capacity Loss Degree of Vanadium Redox Flow Battery Based on Probabilistic Neural Network

Abstract:

During long-time charge-discharge cycling, the capacity of the vanadium redox flow battery (VRFB) will reduce gradually. To recognize the capacity loss condition in the time of the operation process, a method for classification of the capacity loss degree based on Probabilistic Neural Network (PNN) is presented. The network inputs are the value of the voltage per second and the average power of the cell stack in any two minutes of the circulation. The network will give out three classes in form of three numbers to classify the capacity loss degree into different levels. The network is trained and validated by experimental data and the results show that the network is suitable for the classification problem of VRFB capacity loss and the method is useful to determine whether the capacity is sufficient and when to restore the cell capacity in real time.

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Periodical:

Applied Mechanics and Materials (Volumes 448-453)

Pages:

2872-2878

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.448-453.2872

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Online since:

October 2013

Authors:

Hong Fei Cao*, Xin Jian Zhu, Hai Feng Shen, Meng Shao

Keywords:

Capacity Loss, Classification, Probabilistic Neural Network, Vanadium Redox Flow Battery

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