Project SCAFFold (Safety Critical Avionics for Future Flight)
In order to deal with key challenges facing mankind, the future of aviation must change radically. Reduction of emissions, more electric aircraft, and autonomous systems are essential to meet these challenges. Autonomous drones will be increasingly used for commercial applications such as delivery of medicines, remote community logistics, and electric powered aircraft will be developed to reduce pollution and congestion in cities. SCAFFold will demonstrate how new autonomous technologies can meet and conform to existing well defined safety standards whilst exploiting the latest technology from neighbouring sectors. Advances from the consumer electronics sector (such as miniaturised sensing, more capable processors, advanced user interfaces) can then be safely and cost-effectively integrated within the flight control system.
Manned aircraft are very reliable and provide the safest means of transport. This reliability is only possible through the use of extremely rigorous quality control, which is very expensive. In order to achieve equivalent levels of safety but at significantly reduced cost, Distributed Avionics have developed a new network-based control system architecture with high levels of robustness, and therefore reliability, at low cost.
Distributed Avionics’ solution is directly applicable to UAS, UAM, and Civil applications and will be a key enabling technology in the shift to all electric, more connected aircraft. The solution achieves this reliability improvement through a novel, patented Masterless control architecture which forms the backbone of a no single point of failure (SPoF) control system. The removal of SPoFs reduces the requirement for highly reliable individual components, which are expensive to produce and challenging to integrate and evolve. For cost sensitive aerospace applications such as UAS and UAM, this approach offers clear advantages, where traditional aerospace products are too expensive to form a sound economic use case.