Project description
A new landing gear system for small aircraft to improve safety and lower costs
Innovative technologies are applied by the aviation industry to improve safety and decrease costs. The E-LISA project is funded within the framework of the CS2 Joint Undertaking, a public-private partnership set up to strengthen European aero-industry collaboration, global leadership and competitiveness. The project will design, produce, test and qualify an innovative Iron Bird for integration tests of an electromechanical actuator (EMA) and an electric brake for Small Air Transport application. The Iron Bird will be able to realistically and inclusively reproduce the landing gears test cases required by certification specifications. It will consist of a multi-functional smart test installation combining hardware and software allowing the execution of all fundamental tests and analyses of the electromechanical landing gear. Big Data available from the tests will allow further development of a health monitoring and prognostic scheme.
Objective
The E-LISA project is aimed at developing, manufacturing, testing, and qualifying an innovative Iron Bird for integration tests of EMA actuator and electric brake for SAT application. The E-LISA Iron Bird will be able to reproduce in a realistic and comprehensive way the landing gears test cases, foreseen by certification specifications and topic leader requirements. It will consist in a multi-functional intelligent test facility integrating hardware and software allowing performing all the tests and analyses perceived as fundamental to demonstrate the maturity of an electro-mechanical landing gear, hence paving the way for its implementation in a small passenger aircraft.
This with the purpose of advancing more electric LG Brake systems and Electro Mechanical Actuators for Landing Gear Systems to above TRL5, in respect with mitigation of safety risks and cost reductions along the certification phase.
Along the execution of the reliability tests, a Health Monitoring a Prognostic framework, from the EMA and Brake linked projects, will be further developed, tuned and refined, thanks to the availability of big data coming from the tests. To this purpose a methodology suitable for deep learning from big data obtained from the test campaign will be developed and applied for reaching project goals. Special care will be dedicated to the assessment of the effective application of proposed innovative technologies since the early stages of design. Although E-LISA Consortium has the necessary heritage and skills to provide and improve already qualified state-of-the-art solutions that the consortium members have developed for previous and ambitious projects, the applicants will purse to goal of going beyond state of art by proposing and developing advanced innovative solutions, some of them in the frame of Industry 4.0 KET (Key Enabling Technologies).
Fields of science
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesdata sciencebig data
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
Keywords
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
10129 Torino
Italy