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 accurate-ly reflect the performance of solar cell under conditions of high altitude, which may have a bad impact on the ap-plications 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, char-acteristics of the short-circuit current of the solar cell were studied in the high altitude, and then with the devel-opment 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. Ac-cording 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.