ABSTRACTThe increasing use of unmanned aerial vehicles in areas such as rescue, mapping, and transportation have made it necessary to study more accurate techniques for calculating flight time estimates. Such calculations require knowing the battery discharge profile. Simplified flight time calculation methods provide data with uncertainties as they are based solely on manufacturer datasheet information. This study presents a setup to measure the battery discharge curve using a LabVIEW interface with a low-cost acquisition system. The acquired data passes through a nonlinear optimisation algorithm to find the battery coefficients, which enables the more precise estimation of its range and endurance. The great advantage of this model is that it makes it possible to predict how the battery will discharge at different rates using just one experimental curve. The methodology was applied to three different batteries and the model was validated with different discharge rates in a controlled environment, which resulted in endurance lower than 3.0% for most conditions and voltage estimation error lower than 3.0% in operational voltage. The work also presented a methodology for estimating cruise time based on the current used during each flight stage.
PREDICTION OF LI-ION BATTERY DISCHARGE CHARACTERISTICS AT DIFFERENT TEMPERATURES AND DISCHARGE RATES BASED ON A HYBRID SOC ESTIMATION APPROACH