AI & Mechanical System Center, Institute for Advanced Engineering, Youngin-si 17180, Republic of Korea.
Sensors (Basel). 2023 Feb 23;23(5):2483. doi: 10.3390/s23052483.
In this paper, an optimal design model was developed to reduce noise and secure the torque performance of a brushless direct-current motor used in the seat of an autonomous vehicle. An acoustic model using finite elements was developed and verified through the noise test of the brushless direct-current motor. In order to reduce noise in the brushless direct-current motor and obtain a reliable optimization geometry of noiseless seat motion, parametric analysis was performed through the design of experiments and Monte Carlo statistical analysis. The slot depth, stator tooth width, slot opening, radial depth, and undercut angle of the brushless direct-current motor were selected as design parameters for design parameter analysis. Then, a non-linear prediction model was used to determine the optimal slot depth and stator tooth width to maintain the drive torque and minimize the sound pressure level at 23.26 dB or lower. The Monte Carlo statistical method was used to minimize the deviation of the sound pressure level caused by the production deviation of the design parameters. The result is that the SPL was 23.00-23.50 dB with a confidence level of approximately 99.76% when the level of production quality control was set at 3σ.
本文开发了一种优化设计模型,以降低用于自动驾驶汽车座椅的无刷直流电机的噪声并确保其转矩性能。通过无刷直流电机的噪声测试,开发了一个使用有限元的声学模型,并对其进行了验证。为了降低无刷直流电机的噪声,并获得可靠的无声座椅运动优化几何形状,通过实验设计和蒙特卡罗统计分析进行了参数分析。选择无刷直流电机的槽深、定子齿宽、槽开口、径向深度和底切角度作为设计参数分析的设计参数。然后,使用非线性预测模型确定最佳的槽深和定子齿宽,以保持驱动转矩并将声压级最小化至 23.26dB 或更低。使用蒙特卡罗统计方法最小化设计参数生产偏差引起的声压级偏差。结果表明,当生产质量控制水平设置为 3σ 时,SPL 为 23.00-23.50dB,置信水平约为 99.76%。