Open AccessFault diagnosis of DC-DC module of V2G charging pile based on Fuzzy Neural Network
Author(s) -
Qunfei Wang,
Xiaoli Lü,
Dongjunming Yang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/772/1/012027
Subject(s) - pile , artificial neural network , fuzzy logic , fault (geology) , computer science , electrical engineering , engineering , artificial intelligence , geology , algorithm , seismology
Aiming at the problem of fault diagnosis of switching devices in DC/DC module of V2G charging pile, a diagnosis method based on fuzzy neural network is proposed. The method combines fuzzy mathematics with neural network, adopts 4-layer forward network and a step degree optimization algorithm, uses the self-learning and self-adaptive ability of neural network, adjusts the parameters of fuzzy set membership function in real-time, and trains a set suitable for V2G charging Fault diagnosis algorithm of DC/DC module of electric pile. Simulation results show that the fault diagnosis algorithm based on fuzzy neural network can effectively diagnose faults.