Research on SOC estimation of lithium battery based on GWO-BP neural network

摘要

Aiming at the problem of inaccurate estimation of state of charge (SOC) in lithium battery applications, this paper proposes a SOC estimation model based on Grey Wolf Optimizer (GWO) and BP neural network. This model takes the terminal voltage and discharge current of the lithium battery as the input terms of the neural network and the battery SOC as the output term. The traditional BP diagnostic model and the new model are trained and tested by using the test data at different discharge rates. Experiments with measured data indicate that compared with the traditional BP neural network, the estimation model proposed in this paper has higher accuracy of SOC estimation and smaller relative error.