Research on SOC fuzzy weighted algorithm based on GA‐BP neural network and ampere integral method

N Guo, Y Fang, Z Tian, S Cao - The Journal of Engineering, 2019 - Wiley Online Library
N Guo, Y Fang, Z Tian, S Cao
The Journal of Engineering, 2019Wiley Online Library
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 …
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.
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