Prediction of the state of charge of battery based on improved LMBP neural network method
WANG Xiaoxuan;HOU Guanjun;SUN Sihao;Xilingol Ultra High Voltage Power Supply Bureau, Inner Mongolia Electric Power (group) Co., Ltd.;
An improved LMBP neural network model is used to predict the state of charge(SOC) of lead-acid batteries for solving the problems of short lifespan and low utilization rate of the valveregulated lead-acid batteries caused by excessive charging and discharging in the substations. This model could improve the computing speed and precision, extend the life of batteries and increase the utilization rate of batteries. In addition, a simulation of the discharge process is conducted using Matlab, and the results prove that the improved LMBP neural network model can effectively improve the estimation precision of the SOC and extend the lifespan of batteries.
【CateGory Index】： TM912