摘要
在对多地电动公交车充电站实地考察后研究发现,在提高估算SOC精度的基础上,将会减轻充电站对区域电网负荷的影响。该文首先通过遗传算法对BP神经网络进行优化,并以此模型来预测动力电池的SOC,提高了预测精度;其次结合剩余电量预测的研究提出充电控制策略;最后进行仿真验证,结果表明该方法在提高SOC预测精度的前提下,起到了削峰填谷的作用,降低了充电站对区域电网的影响。
After the field study on the multi-ground electric bus charging station,it is found that the influence ofthe charging station on the regional grid load will be alleviated on the basis of improving the estimated SOC precision.In this paper,the BP neural network is optimized by genetic algorithm,and the model is used to predictthe SOC of the battery,and the prediction is improved.Secondly,the charge control strategy is proposed.Improvethe accuracy of SOC prediction under the premise of played a peak load shifting effect,reducing the impactof the charging station on the regional power grid.
作者
王震
陈耀
徐悦
Wang Zhen;Chen Yao;Xu Yue(College of Electrical Engineering and Automation,Shandong University of Science and Technology,Shandong Qingdao 266590)
出处
《电子质量》
2017年第2期1-3,29,共4页
Electronics Quality
关键词
SOC
BP神经网络
遗传算法
控制策略
SOC
BP Neural Network
Genetic Algorithm
The control strategy
