量化了城市空域中eVTOL避撞的能耗成本,发现多数飞行影响极小。
eVTOL Aircraft Energy Overhead Estimation under Conflict Resolution in High-Density Airspaces

- 用物理功率模型结合交通仿真,评估MVP算法避撞能耗
- 95%场景能耗增加低于5.3%,最高仅44%但属极端情况
- 开发可预测能耗范围的机器学习模型,适合安全规划
电动垂直起降(eVTOL)飞机在高密度城市空域运行时需通过战术避撞保持安全间距,但此类机动的能耗尚未系统量化。本文研究基于改进电压势(MVP)算法的避撞操作对eVTOL能耗的影响。利用集成物理功率模型的交通仿真,分析了约71,767个航段,覆盖10至60架同时飞行器的流量密度。主要发现:MVP避撞具有能量效率优势,所有密度下中位能耗增加均低于1.5%,多数航段几乎无额外能耗;但分布呈显著右偏,高密度下尾部案例能耗可达44%。第95百分位为3.84%至5.3%,表明预留4%-5%能量余量可覆盖绝大多数避撞场景。为此,我们构建了可在任务初始阶段估算能耗的机器学习模型,能提供点估计与不确定性边界。这些边界保守,实际结果落入预测范围的概率高于声明置信度,适用于安全关键的能量储备规划。结果验证了MVP算法在能量受限的eVTOL运行中的适用性,并为先进空中交通提供了定量能量储备依据。
原文摘要 · Abstract (English)
Electric vertical takeoff and landing (eVTOL) aircraft operating in high-density urban airspace must maintain safe separation through tactical conflict resolution, yet the energy cost of such maneuvers has not been systematically quantified. This paper investigates how conflict-resolution maneuvers under the Modified Voltage Potential (MVP) algorithm affect eVTOL energy consumption. Using a physics-based power model integrated within a traffic simulation, we analyze approximately 71,767 en route sections within a sector, across traffic densities of 10-60 simultaneous aircraft. The main finding is that MVP-based deconfliction is energy-efficient: median energy overhead remains below 1.5% across all density levels, and the majority of en route flights within the sector incur negligible penalty. However, the distribution exhibits pronounced right-skewness, with tail cases reaching 44% overhead at the highest densities due to sustained multi-aircraft conflicts. The 95th percentile ranges from 3.84% to 5.3%, suggesting that a 4-5% reserve margin accommodates the vast majority of tactical deconfliction scenarios. To support operational planning, we develop a machine learning model that estimates energy overhead at mission initiation. Because conflict outcomes depend on future traffic interactions that cannot be known in advance, the model provides both point estimates and uncertainty bounds. These bounds are conservative; actual outcomes fall within the predicted range more often than the stated confidence level, making them suitable for safety-critical reserve planning. Together, these results validate MVP's suitability for energy-constrained eVTOL operations and provide quantitative guidance for reserve energy determination in Advanced Air Mobility.
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