A Study on Optimization of Noise Reduction of Powered Vehicle Seat Movement Using Brushless Direct-Current Motor

Area of Science:

• Engineering
• Acoustics
• Automotive Technology

Background:

• Brushless direct-current motors are crucial for autonomous vehicle seats.
• Noise and torque performance are key considerations for passenger comfort and system reliability.
• Existing designs may not adequately address acoustic challenges in this application.

Purpose of the Study:

• To develop an optimal design model for brushless direct-current motors in autonomous vehicle seats.
• To reduce noise levels while ensuring torque performance.
• To achieve reliable optimization geometry for noiseless seat motion.

Main Methods:

• Developed and verified an acoustic model using finite elements.
• Performed parametric analysis using Design of Experiments and Monte Carlo statistical analysis.
• Selected key design parameters: slot depth, stator tooth width, slot opening, radial depth, and undercut angle.

Main Results:

• Determined optimal slot depth and stator tooth width using a non-linear prediction model.
• Achieved a minimized sound pressure level (SPL) of 23.26 dB or lower.
• Utilized Monte Carlo simulation to minimize SPL deviation due to production variations, achieving 23.00-23.50 dB at 3σ with 99.76% confidence.

Conclusions:

• The proposed optimal design effectively reduces noise in brushless direct-current motors for autonomous vehicle seats.
• The methodology ensures torque performance is maintained alongside noise reduction.
• The study provides a robust approach for designing quieter and more reliable automotive seat motors.