The 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.

中文翻译：

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测量电池放电特性以准确估算无人机的续航时间

在救援、测绘和运输等领域越来越多地使用无人机，因此有必要研究更准确的技术来计算飞行时间估计。此类计算需要了解电池放电曲线。简化的飞行时间计算方法提供的数据具有不确定性，因为它们仅基于制造商数据表信息。本研究提出了一种使用带有低成本采集系统的 LabVIEW 接口测量电池放电曲线的设置。获取的数据通过非线性优化算法找到电池系数，从而更精确地估计其续航里程和续航时间。该模型的最大优势在于，它可以仅使用一条实验曲线来预测电池如何以不同的速率放电。该方法应用于三种不同的电池，并在受控环境中以不同的放电率对模型进行了验证，结果在大多数条件下，耐久性低于 3.0%，工作电压下的电压估计误差低于 3.0%。这项工作还提出了一种基于每个飞行阶段使用的电流来估计巡航时间的方法。