高精度锂离子电池组电压采集及荷电状态预测  

High Precision Battery Voltage Acquisition System Design and SOC Prediction

作　　者：邹浩[1] 于仲安[1] 赵凯贤 何俊杰[1] 

机构地区：[1]江西理工大学电气工程与自动化学院,赣州341000

出　　处：《科学技术与工程》2017年第5期208-212,共5页Science Technology and Engineering

基　　金：国家自然科学基金(51177066);江西省教育项目(GJJ150678)资助

摘　　要：为了进一步提高锂离子电池组单体电池电压采集精度和荷电状态(SOC)预测精度,设计了优化型串联母线电压采集系统和改进型灰色非等间隔灰色模型SOC预测。电压采集系统通过光耦电路把电池动态加载到母线上,利用74HC595移位控制寄存器实现单体电池电压采集;再经过信号转换、隔离电路处理后由STM32F103ZET6 AD模块处理。SOC预测通过MATLAB建立模型,模型中的参数辨识采用粒子群优化算法。仿真和实验表明,设计电压采集系统硬件电路和软件操作更为简化,采集精度更高,易于拓展,SOC预测方法准确性高,有很强的工程适用价值。In order to improve lithium ion battery monomer voltage acquisition accuracy and state of charge pre-diction accuracy further. A optimized serial bus voltage acquisition system is designed and improved grey interval grey model to predict the SOC. In the voltage acquisition system, the photoelectric relay circuit is adopted to load a battery on the measurement bus dynamically, and the voltage monitoring is measured by means of the logic control of shift register 74HC595, then dealing by the signal conversion and isolating circuit, at last by STM32F103ZET6 analogue-to-digital conversion module processing. SOC prediction by MATLAB to establish model, and model pa-rameters are figured by particle swarm optimization. Simulation and experiment show that the voltage acquisition system simplifies the hardware circuit and software operation, higher precision, easy to expand, SOC prediction method has higher accuracy, meet the demand of practical application.

关 键 词：锂离子电池 测量母线 光耦隔离 动态加载 灰色预测 粒子群优化算法 

分 类 号：TM912[电气工程—电力电子与电力传动]