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摘要:
高空条件下太阳电池特性测试对于研究航天用太阳电池具有重要意义。本文提出了一种高空太阳电池Ⅰ-Ⅴ特性曲线测量方案，研究基于FPGA的硬件测试系统、并行数据采集测量方式和系统软件自动测量方法。提出基于混沌算法与遗传算法融合的太阳电池Ⅰ-Ⅴ特性曲线拟合算法。针对地面测试实验数据，利用太阳电池单二极管数学模型进行曲线拟合计算，结果表明混沌遗传算法优化结果适应度值为4.0289×10-4，曲线拟合效果优于粒子群算法和遗传算法。
Abstract:The high altitude calibration of solar cells is of great significance to study solar cells for space application. This paper presents a measurement scheme to measure the Ⅰ-Ⅴ curves of solar cells at a high altitude. The paper studies the hardware testing system based on FPGA, the method of acquiring the current and voltage data in parallel and the automatic measurement method of software in this system. An algorithm for fitting the current-voltage curve of solar cells based on chaos algorithm and genetic algorithm is proposed. According to the experimental data of ground testing, the curve fitting algorithm is carried out by using solar cell single diode mathematical model. The results show that the fitness value of the chaos genetic algorithm is 4.0289×10-4, which means that the curve fitting is better than particle swarm algorithm and genetic algorithm.
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Key words:
- solar cell /
- Ⅰ-Ⅴ characteristic test /
- chaos genetic algorithm /
- curve fitting
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Abstract: Solar cell is an important part of the energy of spacecraft, and the accurate calibration of solar cell can provide data reference for the assembly of solar panels. The ground solar simulator may bring in error, and can't accurately reflect the performance of solar cell under conditions of high altitude, which may have a bad impact on the applications of solar cell in space. So it has a very important significance to research calibration technology of the solar cell under conditions of high altitude. Originated in the United States, high altitude solar cell calibration technology is mainly applied to study the performance of solar cells in high-altitude environment. Initially, characteristics of the short-circuit current of the solar cell were studied in the high altitude, and then with the development of science and technology, the Ⅰ-Ⅴ characteristic curve of the solar cell was measured. China is still in the primary stage of high altitude solar cell calibration technology, and only two kinds of exploratory solar cells short-circuit current tests were carried out.
Taking the imperfection of high altitude solar cell testing technology, and insufficiency of theoretical research into consideration, we focused on the key technologies of high altitude solar cell testing and calibration methods. Research for the power generation mechanism and electrical characteristics of the solar cell was carried out. According to the test environment, the key technologies and methods of Ⅰ-Ⅴ characteristics of solar cells in high-altitude environment were introduced. An Ⅰ-Ⅴ characteristic test system based on programmable electronic load for solar cells was designed, which could execute tests on solar cell automatically.
According to the measurement error of experimental data, the curve fitting algorithm was developed to get more accurate Ⅰ-Ⅴ curve data. On the basis of the analysis of equivalent mathematical model of solar cells, a method based on chaotic genetic algorithm was proposed to fit the Ⅰ-Ⅴ curve of solar cells. In view of the solar cell's Ⅰ-Ⅴ characteristics data, the algorithm, which provided the value of the parameters of the equivalent mathematical model, was executed to achieve curve fitting. The fitness value of the chaos genetic algorithm is 4.0289e-4. The comparison results show that curve fitting with chaotic genetic algorithm is better than particle swarm algorithm and genetic algorithm. Based on the equivalent mathematical model of solar cell, the characteristic parameters of solar cells corresponding to experimental conditions can be calculated.
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图 2 IIC读写仿真. (a)写操作仿真. (b)读操作仿真.
Figure 2. Read and write simulation of IIC bus. (a) Write operation simulation. (b) Read operation simulation.
表 1 算法对比.
Table 1. Algorithm comparison.
Algorithm GA PSO CGA Iph/A 0.11779 0.11758 0.11606 ISD/μA 0.43747 0.49006 0.06546 n 1.65982 1.67546 1.44324 Rs/Ω 0.04234 0.02183 0.10352 Rsh/Ω 303.839 185.985 239.432 RMSE 6.1302e-4 7.1745e-4 4.0289e-4 
下载: 导出CSV
表 2 太阳电池特性参数.
Table 2. Characteristic parameters of solar cell.
Parameters Value Isc/A 0.11601 Voc/V 0.53004 Pm/W 0.04478 Im/A 0.10506 Vm/V 0.42627 FF 0.7283
下载: 导出CSV
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