Modeling and analysis of non-circumferential symmetric permanent magnet spherical motor using genetic algorithm-based...

Area of Science:

• Robotics and Control Systems
• Electromagnetism and Magnetic Devices

Background:

• Permanent magnet spherical motors (PMSpMs) are complex multi-degree-of-freedom devices.
• Accurate torque modeling is crucial for controlling PMSpMs, especially those with non-circumferential symmetric magnets.

Purpose of the Study:

• To develop and validate a torque map-based torque model for PMSpMs with non-circumferential symmetric magnets.
• To introduce a genetic algorithm-based approach for calculating reversal torque and improving real-time performance.

Main Methods:

• Analytical modeling of the 3D magnetic field using the spherical harmonic method.
• Formulation of an analytical torque model via the Lorentz force method.
• Development of a torque map-based model and a genetic algorithm for reversal torque calculation.

Main Results:

• The magnetic field model was verified using finite element method (FEM) analysis and experimental radial magnetic flux density measurements.
• FEM and experimental results confirmed the accuracy of the developed torque map-based torque model.
• The genetic algorithm demonstrated effective real-time performance for reversal torque modeling in Qt 5.14/C++.

Conclusions:

• The proposed torque map-based torque model accurately represents PMSpM behavior.
• The genetic algorithm provides an efficient solution for real-time reversal torque calculation.
• The developed models enhance the control and application potential of PMSpMs.