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Human Machine Interface to Power and Energy Network


TECHNOLOGY AREAS: Ground/Sea Vehicles, Electronics


OBJECTIVE:  To develop a semi-autonomous operator's control center for operational power and energy networks in military systems.

DESCRIPTION:  The military has been developing advanced Power and Energy Networks that will allow for more efficient, flexible, and resilient energy security systems.  There is a need to develop the human-machine interface enabling the operator to control and influence the network, ensuring the network is achieving its optimal potential in relevant operational environments. The interface would need to display the state of the system and all components that make up the power and energy network as well as allow for controlling that state, including alerts of power spikes or drains, thermal issues, electrical parameters and discontinuities, and mechanical health.  The interface will display recommendations for steps the operator may undertake to mitigate any problems, ranging from additional focused monitoring to manual emergency shut-down.

Challenges include the development and integration of appropriate models that represent the power and energy system and obtaining accurate sensor information from constituent devices.  Further challenges are displaying the information in an understandable format and allowing for an efficient response time for the operator interaction with the network's mechanics. 

PHASE I:  Catalogue and report the current state of the art cognitive visualization models.  To be included is the human factor engineering specifications of utilizing the visual space and design for optimizing understanding of the network state.  Care should be directed to determining when the network state goes beyond specific metrics requiring human interruption to restore normalcy with suggested actionable options.  Catalogue and report the current state of the art of autonomous technology for power and energy networks and controls.  Report the possible integration points of combining the two areas into a system that would allow for semi-autonomous control of a power and energy system.

PHASE II:  Identify the technical gaps from merging the cognitive visualization with the autonomous tools that engage the user and allow for understanding at an unburdened state.  Begin the process of modeling, prioritizing and solving the gaps to create a system that is adaptable and robust to meet any unanticipated, emergent phenomenon.   Begin preliminary design of system architecture and hardware for the automated control of simple and complex power network, with human-machine information exchange displays and interaction.

PHASE III:  Further expand the utility of the model and the interaction hardware for display and controls. Undergo more rigorous test and evaluation on complex networks likened to large Forward Operating Base, Remote-Austere Airfields, Electric Ships, and vehicles.

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