Examples

PyThrust includes runnable examples that show the main workflows: solving and calibrating propulsion models, inspecting rate-map battery behavior, and using OpenMDAO for hover co-design.

Run examples from the repository root so relative data/ and docs/images/ paths resolve correctly.

PYTHONPATH=. python examples/<example_name>.py

Requirements

Example	Extra dependencies
calibrate_system_resistance.py	Core PyThrust dependencies
rate_map_battery_point_states.py	Core PyThrust dependencies
rate_map_battery_mission.py	Core PyThrust dependencies
select_motor_from_database.py	openmdao
openmdao_hover_optimization.py	openmdao, matplotlib

Install the full example environment:

pip install -e .[plot,openmdao]

System Resistance Calibration

Script:

PYTHONPATH=. python examples/calibrate_system_resistance.py

This example identifies the lumped system resistance for a motor, propeller, fixed-voltage battery, ESC, and wiring setup.

It uses:

Input	Value or source
Motor	Datasheet Kv, resistance, no-load current, and current limit
Propeller	APC_13x6.5E from data/propellers/apc_202602
Battery	Fixed 4S nominal voltage, 14.8 V
Test table	RPM, thrust in grams, and battery current in amps

The output reports:

Metric	Meaning
System resistance	Fitted SystemSpec.resistance_ohm
Thrust RMSE	Propeller-model thrust error against measured thrust
Current RMSE	Battery-current prediction error
Thrust R2	Fit quality for the aerodynamic thrust prediction
Per-point table	Predicted vs measured thrust/current for each RPM row

See Motor Calibration for the calibration model and equations.

Rate-Map Battery Point States

Script:

PYTHONPATH=. python examples/rate_map_battery_point_states.py

This example loads data/batteries/example_liion_cell.json, applies a 4S2P pack topology, and evaluates the same state of charge under several requests.

It demonstrates:

Query	Meaning
state_at_current	Terminal voltage and power at a requested pack current
state_at_c_rate	Current/voltage behavior at a requested cell C-rate
state_at_voltage	Current required to hold a requested pack voltage
state_at_power	Current and voltage for a requested pack power
state_at_load_resistance	Battery behavior under a resistive load
state_at_power_loss	Battery behavior for a requested internal loss power
Infeasible power	How the model reports a power limit

This example is intentionally independent from the propulsion solver. It validates the battery model surface before mission or solver integration.

Rate-Map Battery Mission

Script:

PYTHONPATH=. python examples/rate_map_battery_mission.py

This example couples RateMapBattery to PropulsionSolver over a short segment schedule. Each segment solves the propulsion operating point using the current battery state, reports pack current and voltage, then integrates state of charge from the solved battery current.

It demonstrates:

Step	Meaning
Load cell data	Use data/batteries/example_liion_cell.json with explicit series and parallel counts
Solve segment	Pass battery_state into solve_operating_point(...)
Read outputs	Inspect battery_voltage_v and battery_current_a on OperatingPoint
Advance state	Use integrate_current(...) to update SoC and delivered energy for the next segment

Motor Selection

Script:

PYTHONPATH=. python examples/select_motor_from_database.py

This example combines theoretical co-design with real motor database lookup.

Workflow:

1. Load APC_13x6.5E propeller data.
2. Use OpenMDAO to find an efficient theoretical motor/propeller/throttle combination for hover.
3. Load the brushless motor database from data/motors.
4. Search real motors near the optimized Kv and current requirement.
5. Print the top candidates sorted by winding resistance and weight.

The optimization target is a hover thrust of 4.903 N, approximately 500 gf.

See Component Databases for motor catalog format and query helpers.

OpenMDAO Hover Optimization

Script:

PYTHONPATH=. python examples/openmdao_hover_optimization.py

This example demonstrates OpenMDAO-based propulsion co-design and a parametric Kv sweep.

It performs three stages:

1. Run the baseline propulsion model.
2. Optimize motor Kv, propeller diameter, and throttle for a fixed hover thrust.
3. Sweep Kv and re-optimize diameter/throttle at each point.

The generated plot is saved to:

docs/images/optimize_and_plot_results.png

The plot shows:

Panel	Shows
Power and propeller sizing	Hover battery power and optimized propeller diameter
Control setting and shaft speed	Optimized throttle setting and shaft speed

See Propulsion Solver for the operating-point solver used inside the OpenMDAO component.