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In this research, the influence of tire size and shape on sound radiation in the mid-frequency region was studied. First, the relationship between the structural wave propagation characteristics of a tire excited at one point and its sound radiation was identified by using FE and BE analyses. Then, by using that relationship, the effect of modifying a tire's aspect ratio, width and wheel diameter on its sound radiation between 300 Hz and 800 Hz was investigated. Finally, an optimization of the sound radiation was performed by modification of the tire structure and shape. It was found that most of a tire's structural vibration does not contribute to sound radiation. In particular, the effective radiation was found to occur at the frequencies where low wave number components of the longitudinal wave and the flexural wave first appear.

Tire tread pattern noise is a major source of road noise generated by motor vehicles. Recently, noise control technology has been developing, and low-noise motor vehicles, such as electric vehicles and hybrid vehicles, have been commercialized. The importance of low-noise tires has increased since regulations R117 for tire noise and R51.03 for motor vehicle noise have been strengthened. To evaluate the tire noise in the development stage of motor vehicles, finished products of tires are required; hence, financial and time costs should be invested. Therefore, it is highly useful to predict tire noise levels in the early stages. Recently, a technology to predict the tire pattern noise using a supervised training method of artificial neural network (ANN) has been developed. The tire tread depth is estimated using the shading of the full image of the actual tire, and the leading edge of the contact patch is calculated using tire contact patch images.

In this research, the influence of tire force and moment (F&M) characteristics on vehicle on-center steering performance was analyzed and then how to improve vehicle on-center performance was studied through controlling tire structure design parameter, tread pattern shape and tread grip characteristics. First, the relationship between vehicle on-center steering performance and tire F&M characteristics was identified by comparing vehicle steering measurements and tire F&M measurements. It was found that key factor of tire related with on-center performance is aligning torque at lower slip angles. As the aligning torque at slip angle 1° increases, on-center feel is improved. Second, the influence of tire design parameters on tire aligning torque was studied through F&M finite element (FE) analysis and measurement. It was found that the aligning torque at lower slip angle increases as stiffness of the tread and sidewall decreases.

As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language.