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The networked distributed engine control system of future air vehicles

Authors:
  • Central Scientific Research Insitute of Armaments and Military Equipment of Armed Forces of Ukraine
Preprints and early-stage research may not have been peer reviewed yet.
Slyusar Vadym, DSc, Prof.
MOD of Ukraine
The networked distributed engine control system of future air vehicles
The future distributed engine control system (DECS) of air vehicle should be
built on the base of networking principle as the part of an integrated, hierarchical,
multidimensional and multiple networks system on the air vehicle board.
As the prototype of the DECS can be used NATO Generic Vehicle
architecture (NGVA, STANAG 4754), which is used in combat vehicles, and the
similar approach - in the GVA Standard of UK or VICTORY Architecture of
combat vehicles in USA. But DECS should combine of multiple networks such as
control network, diagnostic and maintenance network to transfer sensors data and
video streams from different high resolution cameras in the space around of
engines and has a full integration with firefighting network, thus such network use
the same sensors and control object as DECS.
In this regard for the transfer of control and feedback data inside the DECS
the current trend is the use of Real-time Data Distribution Service (DDS) over a
wireless IP network (also used in NGVA) based on ROS-2 (Robotic Operating
System) or a similar version of ROS-M. As the dissemination protocol of data can
also use combination of DDS with MQTT-SN, which is a publish/subscribe
messaging transport that was designed for vehicle-to-vehicle telemetry, sensors
networks and is now a major protocol of IoT. To reduce jitter and latency of engine
control networks can be used the integration of DDS with Time-Sensitive
Networking (DDS-TSN), which will have the jitter on a level not more as few
microseconds.
To the building of EMP-tolerant and fault-tolerant engine control networks
and high temperature-compatible communications need use fiber-optic engine
control networks. In this context the best solution is use few SOSA single board
computer units and SOSA Input-Output modules with fiber-optic connectors. Such
connectors have maximum transfer speed 22 Gbod and all SOSA units are full
ruggedized. Worth saying, that on this time the SOSA standard is shared only for
USA citizen, but in the future it will be expand to other countries. Each network
inside DECS (control network, diagnostic and maintenance network, firefighting
network) need have one or few distributed SOSA single board computer units with
gateway between such networks inside DECS and gateway to other networks of air
vehicle beyond DECS. For better compatibility networks on board air vehicle need
expand general principles building of DECS (common DDS-TSN Data model etc.)
to all hierarchy of such networks.
Because Artificial Intelligence (AI) is the basis of future control networks, the
implementation of AI is an important trend in the development of the future DECS.
AI is useful in particular with respect to making heterogeneous control systems
work together; to improve data exchange to working with fewer resources of data;
to making coordination of sensors, actuators, and controllers onboard air vehicles,
threat detection and identification. AI can also perform inside DECS the following
functions: warnings about the possibility of a critical situation, determining a safe
mode of an engine working, detecting suddenly emerging threats that impede
engine functionality, visual warning for marking areas requiring special attention,
the analysis of hyper spectral images of the local zones of the engine to identify
changes in its surface, which is a sign of possible destruction, identification against
the backdrop of natural wear. AI is a means of improving timeliness (fast threat,
pop up, numerous threats), derivation of intents, situational awareness and
evaluation. On the other hand, as a communication bridge and feedback
mechanism from AI to a Human for the support of decisions making should be
used Augmented Reality (AR) technologies. For this task can be used the cloud or
multi-network cooperative AI algorithms, which is distributed between several
networks and systems of air vehicle and can design joint three-dimensional
outlines AR visions for the common situation awareness picture.
In this regards, it is about the need for interoperability between the format
(model) of data that is generated at an engine networks and the software of AR
symbols playback devices, which must identify the type of data, and send it to the
display (visual data), speakers (acoustic symbols) or tactile elements (gloves, belts,
etc.). In some cases, engine data can be transformed into AR data (and back) in the
DECS. But in most general case, there is a need to exchange AR-specific data or
AR data blocks, because not all AR data is the engine feedback information. For an
example of such a context is AR 3D virtual models of engine for testing engine
systems before mission, anime, avatars, shell symbols of sensors or actuators,
which was recognized by AI on the point cloud and video streams, also some
elements of synthetic environment, etc. All these tasks can be decided by
standardization of an AR data transfer protocol (structure and size of a typical data
block). On the other hand, cross-networks transparent AR data traffic needs to be
transmitted by using cyber and jamming protected communication. In the future,
block chain technology can be used, but the big issue today is limited by
performance of on board communication links. In this context current data transfer
standards via fiber-optics have to be updated on the base of new waveforms and
technologies. One new idea suggests the spread spectrum with not-orthogonal
frequency discrete multiplexing (N-OFDM) of signals. It can increase data
performance by better spectral efficiency.
On board cross-networks sharing of AR data will radically update the learning
and training process for crews on the frameworks of virtually missions. As noted
by other researchers, AR data can be used as virtual combination of live and
synthetic environment elements as well.
The current situation is that existing standards in this area is not fully
developed, i.e. there are several gaps. Moreover, there is no overall and long-term
plan for establishing a set of standards that consider the aspects of interoperability.
Some initiatives and technology trends that are believed to help on the current
situation is under discussion.
The key means to ensure the interoperability of DECS subsystems is thus to
develop DECS standards as a System of Systems of Standards (S3). DECS S3
should represent interoperability, and it is defined in an integrated, hierarchical,
multidimensional and multifunctional system of normative documents.
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