Estimation of Airflow in the Vehicle Engine Room and Velocity of Air Passing Through the Heat Exchanger Using Machine Learning

Takumi Kitsukawa･Fangge Chen･Takehito Teraguchi･Kei Akasaka･Takuya Nanri (Nissan Motor)

To evaluate vehicle thermal performance, Computational Fluid Dynamics (CFD) simulations play an important role, but they are costly and time-consuming. In this study, we propose a surrogate model using machine learning reduce the cost and time associated with CFD. This model estimates airflow in the engine room and the velocity of air passing through the heat exchanger from vehicle shape and airflow resistance of the heat exchanger. We then show the estimation accuracy and the computation time on a self-made dataset, demonstrating the effectiveness of the proposed method.

Research on the Flow Field Structure to Achieve Both Reduction of Snow Adhesion and Aerodynamic Performance

Motoki Morioka･Masatoshi Saitou･Tomohisa Ueda･Hyuuga Miyazawa (SUBARU)

Focusing on the snow adhesion phenomenon at the rear of the vehicle, we analyzed the mechanisms that lead to snow adhesion. Based on our findings, we optimized the wake structure by controlling the airflow from both the underbody and the roof. This study explored technologies aimed at simultaneously reducing vehicle drag and minimizing snow adhesion.

Development of CAE Methods for Predicting Snow Accumulation on Floor Undercovers During Snowy Road

Tadashi Matsuura･Teruyuki Annen･Shigeki Ueno･Takeyuki Harada･Mikio Asai･Haruyuki Watanabe (Toyota Motor)

The use of resin underfloor covers has become widespread in automotive design to enhance aerodynamic performance and fuel efficiency. However, during driving on snowy roads, snow accumulation poses a risk of damaging these covers, necessitating measures to mitigate this issue. This study employs a particle method for analyzing snow accumulation on the covers and proposes an evaluation technique that contributes to reducing the development time and costs in vehicle development.

Flow around a Longitudinal Circular/Square Cylinder Moving Near the Ground

Yuui Mitamura･Firoz Mohammed Rathore･Kazuki Matsuno (Doshisha University)･Tatsuya Inoue (Railway Technical Research Institute)･Katsuya Hirata (Doshisha University)

In order to reveal the ground effect upon vehicles, we conduct wind-tunnel experiments to study the flow on longitudinal circular/square cylinder moving near the ground. As a result, the effect is remarkable at h/D < 1.0, where h and D are cylinder height and diameter respectively. CFD reveals the flow representing the effect.

Investigation of Aerodynamic Drag Differences Caused by Tire Brand Variations and Their Reduction Methods

Yoshiteru Hoshida･Hiroaki Nagaoka･Shin Makita･Yuichi Isobe (Honda Motor)

This study investigates the effect of tire brand variations on the aerodynamic drag coefficient (CD) of the same vehicle. Wind tunnel testing and CFD analysis revealed that differences in sidewall shape are the main cause of CD variation. In particular, the front tire shoulder and cross-sectional profile significantly affect the flow field and contribute to drag differences. Based on these findings, a shape optimization method was proposed to reduce CD variation, and its effectiveness was verified through wind tunnel tests. This presentation reports the mechanism of CD variation and the proposed reduction method.