Estimation of power battery SOC based on firefly BP neural network

doi:10.12028/j.issn.2095-4239.2018.0230

Abstract

Abstract: In view of the defect of BP (back propagation) neural network algorithm of clectric vehicle battery charge state SOC (state of charge) estimation. Taking lithium iron phosphate battery as the test object, the performance parameters of lithium battery were collected on the power battery test system of EVTS electric vehicle manufactured by ARBIN Company. Using terminal voltage and discharge current as input parameters and SOC as output parameters, fa-bp neural network model was established to estimate SOC in any state during charging and discharging of lithium ion batteries. The simulation results show that compared with the existing BP neural network estimation method, the method based on FA-BP neural network has high accuracy and good practicability.

Key words: lithium ion battery, state of charge, firefly algorithm, BP neural network

CLC Number:

U469.722

WU Huawei, ZHANG Yuanjin, YE Congjin. Estimation of power battery SOC based on firefly BP neural network[J]. Energy Storage Science and Technology, 2019, 8(3): 575-579.

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