基于暗特性曲线提取辐伏转换器件特性参数的算法

Algorithm for Extracting Characteristic Parameters of Radiation-Voltage Conversion Devices Based on Dark Characteristic Curve

  • 摘要: 开展辐伏电池理论研究需要计算辐伏转换器件的特性参数,通过特性参数即可预测辐照条件下辐伏转换器件的输出特性,为辐伏电池设计提供重要理论参考。本研究算法基于辐伏转换器件暗特性曲线,计算辐伏转换器件的特性参数,并通过统计学方法分析计算特性参数的优劣。并利用提取出的特性参数预测转换器件在源辐照条件下的特性曲线并与实际测量的辐照特性曲线对比,以证明算法的有效性。结果表明,计算结果在曲线拟合和输出特性预测上均取得了良好的效果。此算法能够在不辐照器件的基础上,通过暗特性曲线预测电池输出特性,可为辐伏电池的设计提供指导。

     

    Abstract: Theoretical research on betavoltaic batteries require calculating characteristic parameters of the radiation-voltage conversion device, in order to predict the output characteristics under irradiation. Through the calculated output characteristics, important theoretical references for the design of betavoltaic batteries are provided. Our algorithm calculates the characteristic parameters of the radiation-voltage conversion device based on the tested dark current-voltage curve and evaluates the quality of the characteristic parameters by statistical methods. To prove the effectiveness of the algorithm, the current-voltage curves under irradiation were predicted, and compared with those obtained by exposing to a real radioactive source. Calculation results achieved good results in both curve fitting and output characteristic prediction of the radiation-voltage conversion device. The results show our algorithm can predict the output of betavoltaic battery through the dark current-voltage curve without irradiation and provide guidance for the design of batavoltaic batteries.

     

/

返回文章
返回