Abstract：A model is created by adopting BP neural network to predict the state of charge of battery, and adaptive genetic algorithm(AGA) is utilized to optimize its weights and bias, to analyze many factors that affecting the battery residual capacity.Finally, with the emulation program written by MATLAB, multiple sets of data are tested and compared with pure BP network and GA-BP network.The results show that the AGA-BP network has a short training time and high accuracy. It is effective for prediction of the any state battery capacity.
冯楠,王振臣,胖莹. 基于自适应遗传算法和BP神经网络的电池容量预测[J]. 计量学报, 2012, 33(6): 546-549.
FENG Nan,WANG Zhen-chen,PANG Ying. BP Neural Networks Based on Adaptive Genetic Algorithms and Its Application to Prediction of Battery Capacity. Acta Metrologica Sinica, 2012, 33(6): 546-549.
2012, Vol. 33 
