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Optimizing the specifications of the parts that make up the vehicle is essential to develop a high performance and quality vehicle with price competitiveness. Optimizing parts specifications for quality and affordability means optimizing various factors such as engineering design specifications and manufacturing processes of parts. This optimization process must be carried out in the early stages of development to maximize its effectiveness. Therefore, in this paper, we studied the methodology of building a database for parts of already developed vehicles and optimizing them on a data basis. A methodology for collecting, standardizing, and analyzing data was studied to define information necessary for specification optimization. In addition, AI technology was used to derive optimization specifications based on the 3D shape of the parts. Through this study, body parts specification optimization system using AI technology was developed.

Recently, customers' demands for future mobility have increased, such as movement in narrow spaces, increased driving freedom, and ease of parking. The key technology to meet these demands is the four-wheel independent steering system. In this study, we introduce the concept design process for a four-corner steering module and how to prove the design. In addition, we introduce a control method for basic driving modes, such as short U-turn, diagonal driving, crab driving, and zero radius turning. Finally, we propose a special driving mode using the instantaneous rotation center of the 4WS system.

The H-point is a critical part of vehicle design as it is the basis for many engineering dimensions within the vehicle interior. A complete design process includes comparisons of the design to competitive benchmark vehicles. However, the competitive design considerations needed to determine the common standard H-point reference are often unknown. The SAE Human Accommodation and Design Devices (HADD) technical committee recently published a new standard benchmark SgRP procedure [2]. This new standard practice needed to be tested with respect to the accuracy and repeatability for determining the unknown h-point design parameters within industry benchmarking tolerances. In 2019, the SAE HADD committee conducted a study to evaluate the reproducibility of the new procedure. This paper presents detailed results of that study and discusses opportunities for applying the new benchmark practice.

Active Sound Design (ASD) allows the Personalized Engine Sound System to be implemented for different types of vehicles and in different geographical regions. While this process is possible, it requires a lot of on-road tuning and therefore is very time consuming. This study presents an efficient way of tuning ASD sounds based on binaural synthesis in a lab environment instead of on-road tuning. The on-road vehicle operating sounds are reproduced by a desktop NVH simulator while the binaural ASD sounds are synthesized by convolving measured Binaural Vehicle Impulse Responses with the output of ASD multi-channel amplifier in real time. A set of binaural recordings on road are compared with the reproduced sound in the lab environment. The comparison results showed the validity of the proposed method for ASD. The main advantage of this approach is the possibility of back-to-back comparison across different ASD tunings.

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications.

Today, many car manufacturers and their suppliers are very interested in power-operated door handles, known as auto flush door handles. These handles have a distinguishing feature in terms of the way they operate. They are hidden in door skins and deployed automatically when users need to open the door. It is obvious that it is a major exterior styling point that makes customers interested in the vehicles that apply it. To make this auto flush door handle, however, there lie difficulties. First, because there is no sufficient space inside a door, applying these handles can be a constraint in exterior design unless the structures of them are kinematic optimized. The insufficient space can also cause problems in appearance of the handles when they are deployed. The purpose of this study is to establish the kinematic system of auto flush door handle to overcome the exterior handicaps such as the excessive exposure of the internal area on the deployed position.