Pre-Pressure Optimization for Ultrasonic Motors Based on Multi-Sensor Fusion

Area of Science:

• Mechanical Engineering
• Robotics
• Materials Science

Background:

• Traveling wave ultrasonic motors (TRUMs) are crucial actuators in various applications.
• Understanding the influence of pre-pressure on TRUM performance is essential for optimization.
• Existing research may not fully address the dynamic interplay between pre-pressure and motor performance metrics.

Purpose of the Study:

• To investigate the impact of pre-pressure on the key performance characteristics of TRUMs.
• To develop an analytical model for simulating pre-pressure effects, including power dissipation.
• To establish a novel optimization criterion integrating multiple performance factors.

Main Methods:

• Development of an analytical model incorporating power dissipation.
• Utilizing an electric cylinder for precise and rapid pre-pressure regulation.
• Conducting simulations and experimental tests to validate the model and findings.
• Integrating stalling torque, maximum efficiency, temperature rise, and speed variance into an optimization criterion.

Main Results:

• Increasing pre-pressure decreases the proportion of the driving zone within the contact region.
• Balanced driving and braking zones lead to lower power dissipation and reduced temperature rise.
• Speed fluctuations decrease with increasing pre-pressure, verified by periodic axial pressure variations.
• The novel optimization criterion achieved a slower temperature rise and lower stationary error within a specific pre-pressure range (260–320 N).

Conclusions:

• Pre-pressure significantly influences TRUM performance, affecting driving zone proportion, power dissipation, and temperature rise.
• A balanced distribution of driving and braking zones is key to efficient operation and thermal management.
• The proposed optimization criterion effectively reduces speed control errors, demonstrating practical applicability.
• Experimental validation confirmed a substantial reduction in residual error with optimized pre-pressure.