Development of Tolerance-Based Performance Prediction Technology and Optimization of Actuator Design Factors of a Magnet Vertical Magnetization of AVAS - Hyun-Ju Lee; Dong-Shin Ko; Deog-Jae Hur (Applied Sciences, 2021)
With the increasing proliferation of electric and hydrogen vehicles, noises to recognize the driving status at low speeds are legalized, so a virtual engine sound generator is required, and slimming is required for packaging it in vehicles. This study investigates an optimization method for improving the electromagnetic force performance and slimming of the magnetic circuit for the permanent magnet structure for the vertical magnetization of the actuator for the acoustic vehicle alerting system (AVAS) of a vehicle and the probabilistic optimization of manufacturing tolerance management. To investigate the impact of the design parameters of the magnetic circuit structure on the electromagnetic force performance and slimming, we performed an independent analysis based on a single variable and investigated the characteristic variations based on multiple variables using a full factorial design and derived a performance prediction regression model using the central composite design of response surface methodology, including the curvature effect, by adding a center point to verify and consider the nonlinear characteristics. Consequently, four effective design parameters were determined to analyze the electromagnetic force performance and slimming of the vertical magnetization structure of the AVAS actuator—permanent magnet thickness, magnetic force collecting plate thickness, yoke position, and yoke thickness. We then performed statistical analysis using Monte Carlo simulation and proposed an optimization management level of 3σ with excellent process capability as the design application tolerance that can occur in the manufacturing process of each design parameter, whereby the confidence level of electromagnetic force performance and slimming improved from 99.46% to 99.73% and 97.62% to 99.73%, respectively.