考虑局部遮挡的太阳能无人机能源控制

针对太阳能无人机在飞行状态下可能出现的太阳能电池局部遮挡情况，开展相应的太阳能电池最大功率点追踪算法和能源控制研究。通过将发光亮度引入相对吸引力计算过程对萤火虫算法进行改进，实现了局部阴影情况下太阳能电池最大功率点的高效追踪。以此为基础，设计了考虑局部遮挡情况下太阳能无人机的太阳能电池/蓄电池混合能源状态机控制规则。以"蒲公英I"无人机为例，建立了太阳能电池阵列模型，开展了考虑局部遮挡情况下太阳能电池最大功率点追踪仿真实验；基于"蒲公英I"飞行剖面，开展了考虑局部遮挡情况的混合能源控制仿真试验。研究结果表明：改进的萤火虫算法可以实现在局部阴影情况下太阳能电池最大功率点的有效跟踪，与萤火虫算法相比收敛时间更短、且功率波动幅度更小；采用改进萤火虫算法和状态机能源管理策略，在考虑局部遮挡的飞行状态下可以实现太阳能电池/蓄电池之间的合理功率分配与控制。

Energy control of solar powered UAVs considering partial shading condition

Aiming at the partial shading conditions of solar cells that may occur in the flight state of solar powered UAVs, the corresponding solar cell maximum power point tracking algorithm and energy control research are carried out. The firefly algorithm is improved by introducing the illuminance into the relative attraction calculation process, achieving the efficient tracking of the maximum power point of the solar cell under the partial shading conditions. Based on this, a solar cell/battery hybrid energy state machine control rule for solar-powered UAVs considering the partial shading conditions is designed. Taking the "Dandelion I" solar-powered UAVs as an example, a solar array model is established, and the maximum power point tracking simulation test of solar cells under the partial shading conditions is carried out. Based on the "Dandelion I" flight profile, a hybrid energy control simulation experiment considering the partial shading conditions was carried out. The results show that the improved firefly algorithm can effectively track the maximum power point of the solar cell under the partial shading conditions, effectively shortening the convergence time and the power fluctuation range compared with the firefly algorithm. With improved firefly algorithm and state machine energy management strategy, reasonable power allocation control between solar cells and batteries can be achieved in the flight state considering shadows.