NEXIO reduces by 30,000 the computation time of the EM simulation of Wifi mapping in aircraft.
Friday, 08 July 2016 Sunday, 07 August 2016EventsEventsFor its seventh consecutive appearance at the Electromagnetic Compatibility International Symposium (11 to 13 July in Rennes), NEXIO is actively involved in the animation and organization of this major event which bring together the academic and industrial experts in electromagnetic compatibility.
Frédéric HOEPPE, head of the Engineering division, co-host the session dedicated to the complex EMC system in which ONERA, XLIM, Cambridge University, ESIGELEC and CNAM participate.
Samuel LEMAN, presents the innovative works which concern the development of a new method for the fast EM simulation of Wifi mapping in aircraft cabin.
Problematic
The implementation of WiFi in an aircraft allows new applications but also new risks of ElectroMagnetic Interference (EMI) on the sensitive electronic equipment. EM simulation tools are very useful for this problematic but usual EM software are not very suitable in early design phase where a lot of variable parameters have to be considered.
To go further, the view of the experts
The Wifi frequencies (2.45GHz) are high compared to the first cavity resonance, the propagation of EM fields strongly depends on the resonant cavity and losses phenomena in the aircraft. Conductivity of the metallic walls, aperture and slots, doors, seats, persons, electronic equipment or cables harness have to be considered in the EM simulation of the system.Taking into account all these phenomena with the usual simulation methods involves very high computational resources which are not compatible with the parametric studies.
Proposed solution
NEXIO has developed an innovative method to quickly identify the EM impact of sensitive parameters such as wifi antennas (number, position) in reverberant environment to optimize the Wifi installation in the aircraft.
This original method for ElectroMagnetic simulation is based on the hybridization of deterministic and statistical models which strongly reduces the simulation time from 8 hours to 1 second (about 30,000 times less).