Ⅰ-Ⅴ characteristic test and curve fitting of high-altitude solar cell

Yuyan Zhang; Yong Liu; Yintang Wen; Xiaoyuan Luo

doi:10.3969/j.issn.1003-501X.2017.07.009

Article navigation > Opto-Electronic Engineering > 2017 Vol. 44 > No. 7 > 725-731

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Yuyan Zhang, Yong Liu, Yintang Wen, et al. Ⅰ-Ⅴ characteristic test and curve fitting of high-altitude solar cell[J]. Opto-Electronic Engineering, 2017, 44(7): 725-731. doi: 10.3969/j.issn.1003-501X.2017.07.009

Citation:

Yuyan Zhang, Yong Liu, Yintang Wen, et al. Ⅰ-Ⅴ characteristic test and curve fitting of high-altitude solar cell[J]. Opto-Electronic Engineering, 2017, 44(7): 725-731. doi: 10.3969/j.issn.1003-501X.2017.07.009

Ⅰ-Ⅴ characteristic test and curve fitting of high-altitude solar cell

1.
Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
2.
Institute of Defense Science and Technology, Yanshan University, Qinhuangdao 066004, China

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Corresponding author: Yuyan Zhang, E-mail: yyzhang@ysu.edu.cn

Received Date 17 May 2017

Revised Date 16 June 2017

Published Date 15 July 2017

Abstract

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.
- solar cell /
- Ⅰ-Ⅴ characteristic test /
- chaos genetic algorithm /
- curve fitting

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References

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Overview

Overview

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.