STTR Phase I: Self-healing Power Electronics for Urban Air Mobility Applications

该小型企业创新研究（SBIR）第一阶段项目的更广泛/商业影响是提高安全性，减轻许多车辆系统和电子设备的重量和冗余。该项目还将在诊断方面加强自主系统集成，并为各种安全关键应用程序进行重新配置。所提出的自愈、容错的电力电子器件具有城市空中交通（UAM）应用之外的巨大市场，并且可以在从运输到太空/航空航天、生物医学设备和微电网的广泛市场中实施。电力电子自诊断故障，从事冗余，重新配置，并保持操作的能力将是基本的，在这样的安全关键应用。 该项目最初将应用于未来最安全、最可持续的城市空中交通工具，提供一流的用户体验，通过减少旅行时间和提高安全性，大大改善美国公民的生活。 潜在的应用和用例包括按需空中出租车、机场班车、个人飞行器、最后一英里交付、空中救护、军事应用和救援任务。该项目的目标是为城市空中交通（UAM）应用创建自愈、高功率密度、可重构和模块化的电力电子转换器（DC/AC逆变器、DC/DC转换器和AC/DC电池充电器）和架构。该项目的主要技术目标是在存在其他几个健康电池和推进电机的情况下，提高电池模块或电机故障的容错能力。第二个目标是探索机器学习技术在DC/AC逆变器和AC/DC充电器应用中的应用。 该项目的第三个也是最后一个目标是研究所提出的自愈模块化电力电子架构对安全关键型UAM应用中电池充电状态、寿命和推进系统性能的影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to increase safety and reduce weight and redundancies for many vehicular systems and electronic devices. This project will also enhance autonomous systems integration in terms of diagnostics and enable reconfiguration for a variety of safety-critical applications. The proposed self-healing, fault-tolerant, power electronics have a large market beyond Urban Air Mobility (UAM) applications and can be implemented in a wide range of markets from transportation, to space/aerospace, biomedical devices, and microgrids. The ability of power electronics to self-diagnose faults, engage redundancy, reconfigure, and maintain operation will be fundamental in such safety-critical applications. This project will initially be applied to the safest and most sustainable Urban Air Mobility vehicles of the future offering best-in-class user experiences that can drastically improve the lives of U.S. citizens by reducing travel time with improved safety. Potential applications and use cases include on-demand air taxis, airport shuttles, personal air vehicles, last-mile delivery, air ambulance, military applications, and rescue missions. The goal of the proposed effort is to create self-healing, high-power-density, reconfigurable, and modular power electronic converters (dc/ac inverters, dc/dc converters, and ac/dc battery chargers) and architectures for Urban Air Mobility (UAM) applications. The main technical objective of this project is to improve fault tolerance in the event of battery module or motor failure in the presence of several other healthy batteries and propulsion motors. The second objective is to explore machine learning techniques in dc/ac inverter and ac/dc charger applications. The third and final objective for this project is to study the impact of the proposed self-healing modular power electronics architecture on battery state-of-charge, life, and propulsion system performance in a safety-critical UAM application. Reliability models that consider healthy and various reconfigured system architectures will be established.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.