Open AccessResearch on SOC fuzzy weighted algorithm based on GA‐BP neural network and ampere integral method
Author(s) -
Guo Na,
Fang Yu,
Tian Zhongli,
Cao Songyin
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9385
Subject(s) - weighting , artificial neural network , algorithm , fuzzy logic , computer science , neuro fuzzy , mathematics , fuzzy control system , artificial intelligence , physics , acoustics
In view of the GA‐BP neural network model for estimating the state of charge (SOC) of batteries be greatly influenced by the voltage sampling accuracy. Here, a SOC estimation model based on fuzzy weighting algorithm is proposed which is modified by combining GA‐BP neural network with ampere integration method. In addition, the block diagram of the fuzzy weighted SOC estimation model and the specific design process of the model and the determination of input and output and the formulation of fuzzy rules are given here. Through comparing the simulation of SOC model based on GA‐BP neural network with the simulation of SOC fuzzy weighting algorithm model based on GA‐BP neural network and ampere integral method, it is concluded that the SOC fuzzy weighting algorithm studied here is superior to the SOC algorithm based on GA‐BP neural network.