Propulsion-system reliability¶
The propulsion model evaluates how the number and placement of operational
motors affects vehicle reliability. Motor state is represented by a sequence in
which 1 means operational and 0 means failed.
Supported configurations¶
| Configuration | Vehicle | Status-vector length |
|---|---|---|
PNPN |
Quadcopter | 4 |
PNPNPN |
Hexacopter, alternating rotation | 6 |
PPNNPN |
Hexacopter, grouped rotation | 6 |
PPNNPPNN |
Octocopter | 8 |
P and N describe the motor rotation direction around the airframe. Because
controllability after a motor failure depends on placement, two vehicles with
the same number of operational motors can occupy different Markov states.
Example¶
from SafeDrones.core.SafeDrones import SafeDrones
model = SafeDrones()
p_fail, mttf = model.Motor_Failure_Risk_Calc(
MotorStatus=[0, 1, 1, 1, 1, 1],
Motors_Configuration="PNPNPN",
Motors_Lambda=0.001,
time=5,
)
Inputs¶
| Parameter | Description |
|---|---|
MotorStatus |
Ordered operational/failed state for every motor |
Motors_Configuration |
One of the supported rotation arrangements |
Motors_Lambda |
Propulsion-unit failure rate, including motor, driver, rotor, and propeller assumptions |
time |
Mission time at which failure probability is evaluated |
Important
Keep MotorStatus in the same physical motor order used by the selected
configuration. Reordering the same zeros and ones may change the result.
Decision support¶
The output can support higher-level logic such as continuing the mission, returning to the station, or initiating a safe landing. The decision thresholds and safety policy remain the responsibility of the integrating system.