蓄电池组智能监测系统及实现SOC值评估方法

Intelligent Monitoring System of Battery Pack and Method for Realizing SOC Value Evaluation

为了提高对蓄电池组的监测能力,通过分层设计将监测系统分为电池组层、采集模块、网络层、主控模块和监控层。构建电池单元的戴维宁模型,提取适合该模型的参数,通过扩展卡尔曼过滤器估算蓄电池组状态参数,保证监测数据的高准确性。将扩展卡尔曼过滤器安插在各个智能采样设备来分散计算量,降低监测系统的负荷。实验结果表明,所提出的方法数据精准度高,在1000测点环境下误差占比只有0.4%。

In order to improve the monitoring capability of battery packs,through layered design,the monitoring system is divided into battery pack layer,acquisition module,network layer,main control module and monitoring layer,which improves the intelligent monitoring capability of battery packs.We construct the Thevenin model of battery cells,and extract the parameters to suit for this model.The state parameters of the battery packs are estimated by the extended Kalman filter to ensure the high accuracy of the monitoring data.The extended Kalman filter is inserted in each intelligent sampling device to disperse the calculation amount and reduce the load of the monitoring system.The experimental results show that the data accuracy of this research method is high,and the error accounted for only 0.4%in the 1000 measuring point environment.