A comparison of MPPT algorithms for hap-solar powered UAVunder different conditions

Nowadays, with the rapid progress of technology, the aviation industry is also developing and shifting to renewable energy sources. With the use of these resources, Solar Powered Unmanned Aerial Vehicles (UAVs) have brought a great innovation to the sector. As a result of the use of the endless energy obtained from the sun in charging the batteries, the flight time of the aircraft has been increased. Environmental conditions cause nonlinear changes in Photovoltaic (PV) output power. Maximum Power Point Tracking (MPPT) is needed in order to supply the battery and avionics on the aircraft with a constant power using the maximum power point at the PV output power. In short, MPPT keeps the voltage of the system close to the maximum voltage obtained from the PV cells under variable conditions. Thus, by ensuring that the maximum power extracted from the PV panel is fed to the battery on the aircraft with a constant current, a longer flight can be achieved and health of the battery can be protected. This thesis study has been prepared with reference to the High Altitude Platform (HAP)-Alpha UAV project developed within German Aerospace Center (DLR). With taking into account the technical features of the UAV used in this HAP Project MATLAB/Simulink models for MPPT have been developed. Afterwards, the MPP tracking efficiencies of Perturb and Observe (P&O), Incremental Conductance (InCond) and Hill Climbing algorithms on the system were investigated for simulated MPPT, which is planned to be used in UAV. The simulation results were compared for different temperature and altitude values, and predictions were made about which algorithm works more efficiently under different conditions.