Saliency-Based Rotor Spatial Position Displacement Self-Sensing for Self-Bearing Machines

Area of Science:

• Electrical Engineering
• Mechanical Engineering
• Control Systems

Background:

• Self-bearing machines utilize magnetic bearings for rotor levitation, requiring precise control of both rotational and spatial positions.
• Conventional methods rely on external sensors for spatial position measurement, increasing system cost, volume, complexity, and failure points.

Purpose of the Study:

• To propose and validate a self-sensing technique for estimating the xy-position of a rotor in self-bearing machines.
• To eliminate the need for external sensors and additional suspension force windings, thereby reducing system complexity and cost.

Main Methods:

• A novel xy-position estimation technique is developed based on the variation of main and cross-inductance.
• The method leverages inductive saliency between two sets of three-phase coils within the machine.
• The technique is applied to a combined winding self-bearing machine, eliminating the need for separate suspension windings.

Main Results:

• The proposed self-sensing method accurately estimates the x and y spatial positions of the rotor.
• Eliminates the requirement for external position sensors, simplifying the machine's design.
• Removes the need for dedicated suspension force windings, further enhancing compactness.

Conclusions:

• The developed inductive-based self-sensing technique offers a viable solution for compact and cost-effective self-bearing machines.
• This approach significantly reduces the number of components and potential failure points compared to sensor-based systems.
• Enables the design of integrated self-bearing machines without external measurement devices or specialized windings.