SBIR/STTR Research Award

Modular, Scalable, Autonomous Energy Management for Next Generation Responsive Space

Award identifier 200dd5ff6cf0121232077574b43eb97300f4183a0c52c039d842a67c2f91727eAwarding agency Department of Defense · Air Force

Award amount

$149,900

Program and phase

SBIR · Phase I

Award year

2012

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
DESIGN NET ENGINEERING LLC
Proposal award date
2011-12-21
Contract end date
Not reported
UEI
P25XMGL8J468
Solicitation number
2011.2
Topic code
AF112-071

Research abstract

ABSTRACT: Next generation highly autonomous space vehicles need certain key technologies in order to achieve their promised goals. Much time is spent in mission planning working out the details of daily activities of space vehicle so as to assure adequate power/energy margin. The more autonomous vehicle must be able to manage power in a proactive rather than reactive way. It is not sufficient to simply notify the C & DH system when the battery is in yellow limit, or shut down non-essential functions when energy reserves are lowa new generation PMAD must take over much of the work previously done on the ground by mission planners. This is similar to ground-based"smart grid"technology. Sources and loads are managed by predictive tools. Design_Net is developing such a system that will support on-orbit autonomous mission executiona system that takes requests from the ground for high-level operations and translates that into a"mission plan."The smart PMAD called"Autonomous Energy Management Subsystem or AEMS starts with a baseline but"learns"operations as the mission proceeds and is able to more highly optimize use of resources. The AEMS depends on a new generation set of modular source and storage which is also being developed. BENEFIT: Cost issues for Space Mission operations look for technology solutions that allow more control and autonomy on board. Likewise, tactical needs seek more direct input into Space Vehicle taskingtasking at a much higher level such as"take a HS image of this Lat/Long ASAP."More modular architectures and components, the ability to add rule based autonomy engines of Spacecraft and the fact the subsystems and components can now have more"smarts"built into them are enablers that allow us to move toward achievement of these larger goals. DNet"s Autonomous Energy Management System (AEMS) is one of the key enablers which will reduce the need for detailed mission planning and move much of that function on-board the space vehicle. Likewise development of the hardware technologies and architectures described in our proposal fill the need for"depot based"rapid configuration of a mission by allowing highly modular energy source and storage components. Our"smart battery"based on Quallion cell technology allows zero maintenance and rapid call up reducing dramatically the cost and maintenance required over traditional approaches.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

21 SBIR/STTR records share this UEI (2003–2016). Reported award amounts total $9,568,915. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.