DATA - Drone Design using AI for Transport Applications

这项为期6个月的可行性研究是由Greenjets有限公司与世界领先的剑桥大学惠特尔实验室合作进行的，旨在为运输领域的定制电子推进发动机开发一种可扩展的人工智能驱动设计，特别是用于先进的空中移动解决方案，即无人机。定制的无人机为各种最后一英里的交付用例提供了优化的性能，与其他车辆相比，降低了能耗和排放。作为一家早期盈利的英国中小企业，Greenjets在缓慢而昂贵的设计过程中面临挑战，阻碍了市场渗透。为了利用不断增长的空对空市场，Greenjets必须在更短的时间内实现最佳定制设计。剑桥大学惠特尔实验室开发了一种结合快速测试和物理参数化的新方法来解决这个问题。该方法的成功实施将使人工智能驱动的决策成为可能，减少设计时间，并使Greenjets能够扩大生产规模，有效地满足不同客户的需求。

This 6-month feasibility study, a collaboration between Greenjets Ltd and the world leading Whittle Laboratory, University of Cambridge, aims to develop a scalable AI-driven design for customised e-propulsion engines in the transport sector, specifically for Advanced Aerial Mobility solutions, i.e. drones.Customised drones offer optimised performance for various last-mile delivery use cases, reducing energy consumption and emissions compared to other vehicles.Greenjets, as an early-revenue UK SME, faces challenges in the slow and expensive design process, hindering market penetration. To capitalise on the growing AAM market, Greenjets must achieve optimal bespoke designs within shorter timeframes.The Whittle Laboratory, University of Cambridge has developed a novel methodology combining rapid testing and physical parameterisation to address this. Successful implementation of this methodology will enable AI-driven decision making, reducing design time and allowing Greenjets to scale production to meet diverse customer requirements efficiently.