ennAIble - zEro emission raNge exteNder AI controled for hyBrid propuLsion systEm

“ennAIble”是由Samad Power和伦敦城市大学构想的一项创新可行性研究，旨在探索将人工智能（AI）和机器学习（ML）技术纳入先进空中机动（AAM）应用中使用的涡轮发电机的设计和控制。该研究探讨了提高这些动力系统的性能、效率和寿命的可行性，这些动力系统是混合动力推进系统和无人机（uav）的重要组成部分。该项目的创新在于弥合人工智能驱动战略与传统的以硬件为中心的汽轮发电机设计领域之间的差距。通过采用数据驱动控制技术，“enable”设想了实时优化系统性能的能力，延长了涡轮发电机的运行寿命，并减少了维护需求。这种潜在的战略转变旨在降低运营成本，提高这些重要航空部件的用户、运营商和制造商的收入潜力。“使能”与关键的国家目标一致，包括英国政府的国家人工智能战略和向净零经济过渡。预计该项目的社会效益将是深远的，能够更快地向难以到达的地点提供医疗服务和应急反应，协助人道主义工作，并有助于提高各部门的生产力。可行性研究经过精心设计，包括全面的项目管理策略、风险缓解计划和财务预测。该研究力求确保物有所值，并最大限度地利用财团内部的共享资源，如知识产权、商业智能和现有设施。总而言之，“启用”是一种利用人工智能潜力优化涡轮发电机技术的开创性方法。凭借其经济、环境和社会优势，该项目旨在加强英国在全球AAM市场的地位，强调公共资金在探索和实现创新和可持续技术方面的作用。

"ennAIble" is an innovative feasibility study conceived by Samad Power and City University of London that explores the incorporation of Artificial Intelligence (AI) and Machine Learning (ML) techniques into the design and control of turbogenerators used in advanced air mobility (AAM) applications. The study investigates the feasibility of boosting the performance, efficiency, and longevity of these power systems, which are vital components in hybrid electric propulsion systems and unmanned aerial vehicles (UAVs).The project's innovation lies in bridging the gap between AI-driven strategies and the traditionally hardware-focused field of turbogenerator design. Through employing data-driven control techniques, "ennAIble" envisages the ability to optimise system performance in real-time, lengthen the operational lifespan of turbogenerators, and reduce maintenance needs. This potential shift in strategy aims to lower operating costs and improve the revenue potential for users, operators, and manufacturers of these vital aviation components."ennAIble" aligns with key national objectives, including the UK government's National AI Strategy and the transition to a net-zero economy. The societal benefits of the project are anticipated to be far-reaching, enabling faster medical deliveries and emergency responses to hard-to-reach locations, aiding humanitarian efforts, and contributing to increased productivity across various sectors.The feasibility study is designed meticulously, including comprehensive project management strategies, risk mitigation plans, and financial forecasts. The study seeks to ensure value for money and maximises the use of shared resources, such as IP, business intelligence, and existing facilities, within the consortium.In summary, "ennAIble" presents a pioneering approach to optimising turbogenerator technologies by harnessing the potential of AI. With its economic, environmental, and societal advantages, the project aims to strengthen the UK's standing in the global AAM market, emphasising the role of public funding in the exploration and realisation of innovative and sustainable technologies.