移动小车电源SOC实时估算系统设计

Mobile Car SOC Real-time Estimation System Design

针对移动小车无法实时显示当前电量,易出现电池过放从而降低电池循环使用寿命的问题,利用Ardu⁃ino作为主控制器采集电池的电压、电流、温度数据,将三者作为BP神经网络的输入量,计算电源SOC值,最后通过LabVIEW平台嵌入该算法实现对电源SOC的实时估算。实验结果表明,神经网络训练误差可满足实际要求,硬件系统整体运行可靠。系统可以实时监测电源的SOC值、电压、电流和温度值,从而避免电源出现异常工作状态,提高电池循环使用寿命。

For the mobile car,the current power cannot be displayed in real time,and the battery over-discharge is easy to reduce the battery cycle life.The Arduino is used as the main controller to collect the voltage,current and temperature data of the battery,and the three are used as the input of the BP neural network.The power SOC value is estimated,and finally the algorithm is embedded in the LabVIEW platform to realize real-time estimation of the power SOC.The experimental results show that the maximum error of 6.88%in neural network training can meet the actual requirements,and the overall hardware system runs reliably.The system can monitor the SOC value,voltage,current and temperature value of the power supply in real time,avoiding the abnormal working state of the power supply and improving the battery cycle life.