A phase-synchronization algorithm for aligning counter-rotating propellers to a reference phase

Background

Multi-rotor aerial and marine vehicles frequently employ co- or counter-rotating propeller pairs to balance torque and enhance efficiency. When two rotors operate in proximity, aerodynamic interference and wake interactions can generate unsteady forces, increased noise, and vibration, degrading flight stability, structural longevity, and thrust performance. Precise synchronization of blade passage angles is therefore critical to minimize unsteady loads, reduce acoustic signatures, and optimize energy consumption in applications such as drones, electric vertical takeoff and landing (eVTOL) vehicles, and contra-rotating marine propellers. Achieving user-defined phase alignment enables more efficient wake cancellation, smoother torque transitions, and improved payload control in increasingly compact and high-speed platforms.

Existing synchronization methods rely on open-loop timing or mechanical couplers, which lack flexibility and struggle to maintain alignment under variable spacing, rotational speeds, and external disturbances. Conventional closed-loop controllers typically regulate only angular speed, failing to enforce specific phase offsets when initial rotor positions differ. Optical or encoder-based phase detection approaches demand intricate calibration, extensive post-processing, and high-bandwidth inter-motor communication that exceed the processing and bandwidth capabilities of embedded flight controllers. Furthermore, sensor latency and timing skew introduce phase estimation errors, hindering robust spatial-temporal coordination and limiting the applicability of current solutions in dynamic flight conditions.

Technology

This technology employs a control algorithm integrated into each motor’s standard PID-based speed controller to continuously measure propeller phase angles and correct for sensor latency using timestamped readings. By computing the instantaneous angular distance to a user-defined reference phase, it dynamically adjusts each rotor’s speed setpoint in real time so both propellers reach the target angle together before resuming nominal operation. Validation is achieved through high-speed camera imaging and MATLAB-based processing—identifying hub centroids, deriving angles via two-point geometry, interpolating phase histories, and using a root-finding routine to confirm crossover accuracy within ±2° at 600–1875 RPM and ±4° at 2000 RPM across multiple rotor configurations.

This approach distinguishes itself by executing a time-bounded, adaptive phase-crossing maneuver rather than maintaining a fixed relative offset, enabling precise alignment even under varying speeds, spacings, and disturbances. Timestamp-based latency compensation obviates the need for synchronized hardware clocks or complex sensor calibration, reducing mechanical and computational overhead. Seamless integration into existing motor controllers allows deployment on low-cost microcontrollers without additional hardware. Automated high-speed video post-validation provides in-situ verification. These features yield higher angular accuracy, broader operational envelopes, simplified architecture and improved vibration and noise reduction compared to traditional open-loop, mechanically linked or PID-only synchronization methods.

Benefits

• Real-time dynamic phase control ensuring both propellers reach a user-defined reference angle simultaneously, even under disturbances
• High angular accuracy (±2° up to 1875 RPM, ±4° at 2000 RPM) for precise synchronization
• Seamless integration into existing PID‐based speed controllers without additional hardware
• Low computational load enabling deployment on cost-effective microcontrollers
• Reduced mechanical complexity by eliminating gearboxes or shafts for counter-rotating systems
• Broad operational envelope validated across multiple rotor spacings and speeds (600–2000 RPM)
• Improved aerodynamic efficiency, reduced vibrations and noise through synchronized blade passages

Applications

• Drone vibration and noise reduction
• eVTOL aerodynamic efficiency optimization
• Helicopter rotor balance control
• Marine propeller cavitation reduction
• Propulsion R&D test automation