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。

The high altitude calibration of solar cells is of great significance to study solar cells for space applica-tion. 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 cur-rent-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.