EnergyTech2015.com SPACE POWER SYSTEMS Track 2 Session 4 Moderator: James Soeder This session explored power technologies being developed to enable more advanced deep space missions including; unique power systems, autonomous and intelligent control and real time simulation Ms Anne McNellis: Paper 1: NASA Intelligent Power Control, Dr Benjamin Loop: Paper 2: Real Time Simulation for NASA Intelligent Power Control Development Dr Brad Glenn: Paper 3: Helm Algorithm Development for NASA Intelligent Power Control

1. National Aeronautics and Space Administration
Intelligent Power Controller
Development for Human Deep Space
Exploration
Anne M. McNelis
NASA Glenn Research Center
Presentation to
Energy Tech 2015
Cleveland, Ohio

2. Agenda
• Overview of NASA’s Deep Space Exploration Vision
• Communication Challenge for Deep Space Vehicle EPS
• Notional Deep Space Vehicle Power Architecture
• Traditional Space Vehicle Control Architecture
• Autonomous Control Architecture
• Objectives of Autonomous Controller
• Mission Manager and Autonomous Control Interface
• Power System Simulations for Test and Verification
• Summary
2

3. The Capability Driven Framework
3

4. 4
4

5. Communication Challenge
5
• Currently EPS systems require
continual support through ground
based mission operations.
• As missions extend beyond LEO,
communication latency time
increases.

6. Space Power Systems
6

7. Notional Deep Space Vehicle Power Architecture
7

8. Traditional Spacecraft Controller Architecture Autonomous Spacecraft Controller Architecture
Transitioning some traditional ground based control functions to
the vehicle
Development of an Autonomously Controlled Spacecraft is consistent with the “Future of Human Space Exploration”
roadmap and enables the transition from “Earth Reliant” systems to “Earth Independent Systems”
Traditional vs Autonomous Spacecraft Controller
8

9. Autonomous Control Objectives
9

10. Simplified Autonomous Control Architecture
10
Autonomous Power Controller
Normal
Mode
Fault Mode
EPS Hardware
Vehicle Manager
Mission Oversight
Vehicle Manager
• Manages operation of overall spacecraft
• Requests power availability from the
Autonomous Power Controller as needed
• Generates Load Schedule based on
power availability
Autonomous Power Controller
• Provides the Mission Manager with
power availability
• Executes Mission Manager load
schedule
• Executes Normal Mode Operation
• Responds and report faults within the
EPS system
EPS Hardware (Reactive Control)
• Provides close-loop control of the power
hardware (BCDU’s, solar array
regulators, Switchgear etc.)
• Accepts control set points from the
Intelligent Controller

11. Intelligent Power Controller
11
National Aeronautics and Space Administration
www.nasa.gov 9
An Intelligent Power Controller utilizes advanced hardware and control
technology and works in conjunction with the spacecraft mission manager
to autonomously manage and control distributed power generation and
storage assets, power distribution networks, and loads for both near earth
and space exploration systems.
Near Earth SystemsExploration Systems

12. Intelligent Control Function Architecture
12

13. Intelligent Control Functions
• Energy Management
– Power availability timeline
– Set points for array regulation,
battery charging / discharging,
– Detect generation and storage
failures
• Power System Model
– Generation model using orbital
parameters
– Energy storage model
– Power load flow
– State Estimator
• Power System Network
management
– Power network security
– Power quality
– Detect soft faults
– Report hard faults
– Configure switchgear
• Power System
Coordination
– Communicate with
Manager
– Coordinate with
identical power channel
entities and/or vehicles
13

14. Power System Fault Management Functions
14
National Aeronautics and Space Administration
www.nasa.gov 16
Assess / Manage Power System
State
• Preventative state -- Normal
operation, continue
indefinitely without
interruption
• Emergency State – Fault
occurs – relieve system
stress and prevent further
deterioration
• Restorative State – System is
degraded but safe – restore
power flow to all loads in a
safe manner in minimum time
Restorative
State
Preventative
State
Emergency
State
Controlled State Transition
Uncontrolled State Transition
Fault Mgmt Functions
• Identify Failures
• Contingency Analysis
• Develop corrective actions
• Component Health Monitor

15. 15
Mission Manager Intelligent Power Control Interface

16. EPS Model Library: Units and Assemblies Systems
ISS
Deep Space Habitat
Battery Cells
PV Cells
Isolating Converter
RPC
RBI
Electrical Power System (EPS) Simulation Development
16

17. National Aeronautics and Space Administration
www.nasa.gov
Control / Distributed
Simulation Platform
• Execute a real-time
state average EPS
• Multi-core PC’s with 8
processors each
• PC’s interconnected
through high speed
Ethernet
• Synchronized via read
write data base via
communication bus
• Capability to interface
with real power
hardware both locally
and remotely
17
Control T&V Simulation Architecture

18. Intelligent Control Development at NASA GRC
• NASA’s Advanced Exploration Systems (AES) Modular Power Systems
(AMPS) projects at GRC are developing intelligent control technologies
for space applications.
– Dynamic EPS Simulations (SBIR with PCKrause and Associates)
• Component, system, direct layer control, failure simulation.
– Autonomous Power Controller (APC) Development
• Distributed Controller, Failure detection (ARC), Power distribution
and loads management, nominal and fault operations.
– Hardware and Software in the Loop Demonstrations Utilizing hardware
testbeds at GRC and JSC
• Interface between APC, Simulink and hardware testbed
components.
18

19. Summary
• Intelligent Power Systems are key for long term missions and
operations far from earth.
• Development of an Autonomously Controlled Spacecraft is
consistent with the “Future of Human Space Exploration”
roadmap and enables the transition from “Earth Reliant”
systems to “Earth Independent Systems”.
• Verification of developmental space EPS autonomous power
controllers will be achieved through real-time EPS
simulations, hardware in the loop and power system test bed
validation efforts.
19

20. 20