Optimization of Flexible Rotor for Ultrasonic Motor Based on Response Surface and Genetic Algorithm

Area of Science:

• Mechanical Engineering
• Materials Science
• Robotics

Background:

• Flexible rotors in traveling wave rotary ultrasonic motors reduce radial friction but face challenges like uneven stator-rotor contact and rotor deformation stress.
• Existing designs require optimization to address persistent issues affecting motor performance and longevity.

Purpose of the Study:

• To develop and validate a novel rotor design for the TRUM60 stator to minimize contact stress and enhance motor performance.
• To introduce an optimization methodology combining Kriging response surface models and multi-objective genetic algorithms (MOGA).

Main Methods:

• Proposed a novel rotor design based on existing structures to complement the improved TRUM60 stator.
• Utilized Kriging response surface modeling with Latin hypercube sampling for data generation.
• Employed a multi-objective genetic algorithm (MOGA) to optimize the Kriging model and identify optimal design solutions.
• Established an objective function targeting the stator-rotor contact surface for optimization.

Main Results:

• The optimization process reduced the objective function value from 0.631 to 0.036.
• Maximum contact stress on the rotor's inner ring decreased significantly from 32.77 MPa to 9.96 MPa.
• Experimental validation confirmed the design's reliability and performance improvements.

Conclusions:

• The integrated Kriging-MOGA optimization method effectively addressed design challenges in rotary ultrasonic motors.
• The novel rotor design enhances stator-rotor interaction, leading to substantial reductions in contact stress.
• This approach significantly improves the overall performance and durability of traveling wave rotary ultrasonic motors.