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Research on dynamic optimal control strategy of distributed super capacitor energy storage system based on convolution neural network
Author(s) -
Li Pengfei,
Chen Hongyun,
Wang Shangshang,
Xu Zhipeng,
Lei Zhenyu
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4873
Subject(s) - supercapacitor , battery (electricity) , computer science , energy storage , artificial neural network , capacitor , automotive engineering , power (physics) , capacitance , engineering , voltage , electrical engineering , artificial intelligence , chemistry , physics , electrode , quantum mechanics
Summary Compared with other modes of transport, urban rail transit has significant advantages such as large capacity, punctual safety, energy saving, and environmental protection. For pure electric buses, the problem of slow start, large battery energy loss, short battery life, and insufficient recovery of braking energy is caused by the use of single energy only. The power battery and super capacitor are combined to form a compound power supply to solve the problem. In order to improve the feature extraction ability of convolution neural networks, a deep convolution neural network model based on continuous convolution is designed. The model uses small scale convolution kernel to extract local features more carefully, and increases the nonlinear expression ability of the model by means of two continuous coiling layers. Dropout technology is used to reduce the interdependence between neurons, and the model is optimized by suppressing network overfitting. If the battery and the supercapacitor are combined to form a dual energy source system, it can not only meet the instantaneous high power demand of the electric vehicle but also prolong the life of the battery. Increasing the mileage of electric vehicles has become the development direction of pure electric vehicles. Due to its fast charging and discharging speed, long cycle life, and friendly environment, supercapacitor has unique advantages and development prospects in solving the problem of urban rail transit regeneration failure, performance analysis, modeling, and parameter identification of ultracapacitor. The performance of ultracapacitor is analyzed, and an improved dynamic equivalent circuit model of ultracapacitor is established. Therefore, this paper studies the control strategy of dual energy source storage system and the driving range of the dual energy source pure electric vehicle, which has a broad application prospect and practical significance.