This paper presents a Multi FPGA- based solution for More Electric Aircraft power systems real-time simulation. The proposed solution allows control and protection devices to be designed and tested in virtual power system before they can be implemented in a physical system. To demonstrate the effectiveness of the multi-FPGA solution, a model approximately representing the Boeing 787 More Electric Aircraft is considered. The B787 power system represents a challenge for any real time simulator. It includes a considerable number of fast and slow switching frequency converters, an extensive number of circuit breakers and very short cables that complicates the power decoupling task.Four complete feeders of the B787 power system are simulated using Dual-Kintex-7 FPGA boards. The controllers and mechanical parts of the Motorized Turbo Compressors are compiled, and real time simulated using a 3.5 GHz Intel processor. The performance of this overall Processor-In-The-Loop integration (PIL) is validated based on two criteria: 1) Evaluation of the results accuracy compared to the reference offline simulation. 2) Evaluation of the numerical stability of the simulation under steady state and fault conditions.

The last decade has witnessed a rising interest in Gossip protocols in distributed systems. In particular, as soon as there is a need to disseminate events, they become a key functional building block due to their scalability, robustness and fault tolerance under high churn. However, Gossip protocols are known to be bandwidth intensive. A huge amount of algorithms has been studied to limit the number of exchanged messages using different combinations of push/pull approaches. We are revisiting the state of the art by applying Random Linear Network Coding to further increase performance. In particular, the originality of our approach is to combine sparse-vector encoding to send our network-coding coefficients and Lamport timestamps to split messages in generations in order to provide an efficient gossiping. Our results demonstrate that we are able to drastically reduce bandwidth overhead and dissemination delay compared to the state of the art.