A Research for AI driven Advanced Performance Evaluation of Exterior Closure System

SOONHO HER･MINHYUNG BYUN･BYUNG SUNG PARK (Hyundai Motor)

To evaluate closure system performance in advance before PROTO/PILOT stage, data for each design parameter involved in certain system is necessary. For implication of data driven advanced evaluation within closure systems, estimation about cabin pressure rise and air bind resistance energy is required. In this paper, cabin pressure rise and air bind resistance energy occurred by slamming door, tailgate or trunk could be estimated by analysis of simple box model and statistical model calibration and validation. With this estimation process, utilizing deep learning technology would be a powerful solution for proto-less and virtual vehicle development to optimize design parameters in advance.

The Role of Interpretability in Shape Generative Models for Aerodynamic Vehicle Design

Daiki Ikeuchi･Yohei Morikuni･Mashio Taniguchi･Yuta Ito･Yuya Fukao･Yuya Yamashita･Shiro Yasuoka･Tomotaka Sugai･Koji Nishikawa･Minoru Tsuchiyama (Toyota Motor)

Deep generative models have demonstrated potential in accelerating aerodynamic design via reduced simulation cost during vehicle development. However, their practical adoption is limited by a lack of interpretability; this challenge obscures decision-making process and complicates the model integration into development workflows. Here, we introduce a technique for visualizing the influence of geometric features on the latent space of shape generative models, offering a pathway towards more interpretable and actionable generative design tools.

Tesla Cybertruck Aerodynamics - A fully automated reverse engineering methodology using 3D Scanning and OpenFOAM

Wouter Remmerie･Nikola Majksner (AirShaper)

Analyzing and understanding the aerodynamics of existing cars is key to improving the shape and efficiency of new cars. 3D scanning is commonly applied to obtain 3D models of cars, but these models pose significant challenges for CFD (computational fluid dynamics) methods - these typically require simplified and watertight models. This paper presents key aspects of a fully automated and validated workflow to analyze the aerodynamics of 3D scans without any manual efforts. The workflow has been validated against wind tunnel test data and has been endorsed by OEMs.

6 Bar Link Operation Analysis Using Multi-body Dynamics

woosik Yoon･Minsu Kim･Sungwon Hong･Jaehyun Seo (DAEDONG HI-LEX)･Kihyun Choi (Hyundai Motors Namyang Laboratory)

With the luxury of automobiles, it is developing from a general side door to a coach door. Since this coach door has a structure without a b-pillar, it requires a lot of rigidity and safety. To this end, a door hinge that can open 0-180 degrees was developed using a six-section link. In this study, the behavior of the 6bar link was analyzed with a Multi-body dynamic. Through this, the operation abnormality according to the distance between the moving pin and the fix pin was confirmed, and a system that improved this could be developed.

Consideration Regarding Drag Torque Reduction of Disc Brakes（2nd Report）

Takumi Inoue･Akinori Hirashima･Naoya Miyahara･Yuhei Yamazaki･Takashi Shimizu･Yusuke Kato (Advics)

One of the characteristics of disc brakes that contributes to fuel effi ciency and electricity consumption isdrag torque.
In this report, the effects of wind flow on drag torque are quantified by CFD analysis for the purpose of reducing drag torque in urban driving, leading to the elucidation of drag torque phenomena and prediction techniques.

Establishment of target aero drag and investment criteria considering vehicle characteristics

WOOKHYUN HAN･KWANG CHAN KO (Hyundai Motor)

The major resistance to vehicle driving energy, known as aero drag, is directly linked to fuel efficiency improvement. To achieve efficient aerodynamic performance development for xEV vehicles with a short history, it is necessary to establish the quantitative relationship between aero drag and fuel efficiency. In this study, we analyze the impact of aero drag reduction on fuel efficiency in internal combustion engines and xEV vehicles. Furthermore, we analyze the aero drag and fuel efficiency effects based on vehicle driving profiles and weights, propose target aero drag, and make decisions on the investment in various aero drag reduction-related items.