万凯歌.基于LabVIEW的新能源汽车充电检测系统设计[J].测控技术,2024,43(12):45-50
基于LabVIEW的新能源汽车充电检测系统设计
Development of New Energy Vehicle Charging Detection System Based on LabVIEW
  
DOI:10.19708/j.ckjs.2024.11.269
中文关键词:  新能源汽车  LabVIEW  数据采集卡  BP神经网络算法
英文关键词:new energy vehicles  LabVIEW  data acquisition card  BP neural network algorithm
基金项目:
作者单位
万凯歌 重庆交通大学 机电与车辆工程学院 
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中文摘要:
      新能源汽车将在交通领域中成为清洁能源替代的理想选择,使用LabVIEW虚拟仪器图形化开发环境作为软件平台,结合PC机和USB-6251数据采集卡等硬件,设计了一款新能源汽车充电检测系统。该系统能够实时检测充电电流、电压和荷电状态(State of Charge,SOC)等关键参数,并对充电过程进行数据记录和分析。该系统应用了反向传播(Back Propagation,BP)神经网络算法,以有效减少数据采集中的干扰并加速采集过程。以三元锂电池为研究对象,在不同温度和AC OFF状态下,根据算法输出曲线与表测曲线的相关波形和重要参数,对车辆的高低温快充测试进行分析。经试验初步验证,该检测系统输出的波形图和数据与充电桩显示的数据一致,显示出良好的实用性。
英文摘要:
      New energy vehicles will become an ideal choice for clean energy replacement in the field of transportation.LabVLEW virtual instrument graphical development environment is used as a software platform,and hardware such as PC and USB-6251 data acquisition card are combined to design a new energy vehicle charging detection system.The system can detect key parameters such as charging current,voltage and state of charge(SOC) in real time,and record and analyze the charging process.The back propagation(BP) neural network algorithm is applied in the system to effectively reduce the interference in data acquisition and accelerate the acquisition process.Taking ternary lithium battery as the research object,the high and low temperature fast charge test of vehicle is analyzed according to the related waveform and important parameters of algorithm output curve and meter curve under different temperature and AC OFF state.Through the preliminary experiment verification,the waveform diagram and data output by the detection system are consistent with the data displayed by the charging pile,and the system shows good practicability.
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