SSOS EPS Demo Documentation

Table of Contents

1. Overview
2. Use Case Motivation
3. System Architecture Design
4. EPS Core Subsystem
5. Simulation Script Descriptions
6. Data and Input/Output Values
7. Assumptions
8. Initial Parameter Source/Reference
9. Setup Instructions
10. Execution and Outputs
11. Validation and Testing
12. Future Work and Extensions
13. Appendix
14. References

---

Overview

The SSOS EPS Demo demonstrates the functionality of the Electrical Power Subsystem (EPS) within the Space Station Operating System (SSOS). This demo includes components such as a power generator, power sink, visualizer, critical load simulation, and the EPS core. It showcases their integration in a ROS-based framework, highlighting modularity, extensibility, and real-time data sharing capabilities.

---

Use Case Motivation

The demo addresses critical challenges in power management for space station systems:

• Ensuring stable power generation and distribution.
• Managing dynamic load demands and prioritizing critical loads.
• Visualizing power flow and system status in real time.
• Demonstrating fault tolerance and recovery mechanisms.

---

System Architecture Design

Overview Diagram

ROS Nodes

1. Power Generator Node (power_generator.py):

   • Simulates the power generation process.
   • Publishes generated power levels to /power_output.

2. Power Sink Node (power_sink.py):

   • Simulates power consumption by various subsystems.
   • Subscribes to /power_output and adjusts consumption based on input.

3. Visualizer Node (visualizer.py):

   • Displays power flow and system status.
   • Subscribes to /power_output and /critical_load_status for visualization.

4. Critical Load Simulation Node (critical_load_sim.py):

   • Simulates the behavior of critical loads.
   • Publishes load demands to /critical_load_demand and monitors status via /critical_load_status.

5. EPS Core Subsystem (eps_core.cpp):

   • Coordinates power generation, consumption, and load management.
   • Provides real-time state updates via /eps/state.
   • Manages interactions with other nodes using abstraction and encapsulation principles.

Interfaces

• Topics:
  • /power_output: Generated power levels.
  • /critical_load_demand: Critical load requirements.
  • /critical_load_status: Status of critical load operations.
  • /eps/state: Current EPS status including energy stored and available power.
• Services:
  • /reset_fault: Resets detected faults in the system.

---

EPS Core Subsystem

Role of EPS Core

The EPS core acts as the central module, coordinating power generation, consumption, and critical load management:

• Abstraction: Provides generic interfaces for power management and load handling.
• Inheritance: Enables specialized nodes to extend core functionalities.
• Encapsulation: Hides internal logic, exposing only APIs necessary for node integration.

Object-Oriented Design

• EPSSubsystem Class: Implements methods for handling power input, sinks, and critical loads.
• Dynamic State Updates: Uses timers to publish real-time state changes to /eps/state.
• Noise and Variability Simulation: Introduces random noise for realistic energy consumption and baseline load variability.

Key Features

• Real-time energy management with dynamic critical load handling.
• Power distribution optimization based on available energy and priorities.
• Fault detection and recovery with configurable thresholds.

---

Simulation Script Descriptions

1. Power Generator Script (power_generator.py)

   • Simulates power generation capabilities.
   • Publishes to /power_output topic.

2. Power Sink Script (power_sink.py)

   • Models subsystem power consumption.
   • Subscribes to /power_output to adjust load dynamically.

3. Visualizer Script (visualizer.py)

   • Displays system-wide power flow.
   • Processes /power_output and /critical_load_status for visualization.

4. Critical Load Simulation Script (critical_load_sim.py)

   • Emulates critical load requirements and operations.
   • Publishes to /critical_load_demand and /critical_load_status.

5. EPS Core Implementation (eps_core.cpp)

   • Manages overall power system state, including energy storage, critical load prioritization, and dynamic updates.
   • Handles interactions with the other nodes via defined topics and services.

---

Data and Input/Output Values

• Topics:
  • /power_output: Reports current power generation levels.
  • /critical_load_demand: Specifies required power for critical loads.
  • /critical_load_status: Provides the operational status of critical loads.
  • /eps/state: Reports current EPS state including energy stored and available power.
• Message Types:
  • std_msgs/Float64 for power values.
  • std_msgs/String for EPS state updates.
  • std_msgs/Bool for critical load statuses.

---

Assumptions

• Power demand profiles are predefined.
• Nodes interact exclusively via ROS topics and services.
• Visualization updates occur at a fixed tick rate.
• Energy storage limits and decay rates are constant during simulations.

---

Initial Parameter Source/Reference

• Power generation limits and efficiency metrics are derived from ESA technical documents.
• Critical load thresholds and priorities are based on NASA mission data.
• EPS core functionality is inspired by industry-standard power management systems.

---

Setup Instructions

1. Install dependencies:

   sudo apt-get install ros-<distro>-desired-packages

2. Clone the repository:

   git clone <repository-url>

3. Build the workspace:

   cd <workspace>
   catkin_make

4. Launch the demo:

   roslaunch eps_demo eps_demo.launch

---

Expected Outputs

• Logs showing power generation, critical load handling, and EPS state updates.
• Real-time visualizations of power flow and load demands.

---

Validation and Testing

• Validation Criteria:
  • Verify power levels adjust dynamically to load changes.
  • Ensure critical load requirements are met under all conditions.
  • Simulate faults and observe system recovery behavior.
• Example Test Case:
  • Simulate a fault in power generation and observe EPS core handling.

---

Future Work and Extensions

• Integration with thermal control subsystems.
• Development of predictive models for power consumption trends.
• Hardware-in-the-loop testing for real-time applications.
• Expand EPS core to handle renewable energy sources in simulations.

---

Appendix

Supplemental Materials

• Power generator flow diagram.
• EPS state machine description.
• Critical load operation timeline.

---

References

1. NASA Systems Engineering Handbook.
2. ROS Documentation: https://www.ros.org
3. ESA Power Management Guidelines.