Evaluation of Vehicle Dynamic Performance on Snowy Roads Using a Driving Simulator and Reforming the Development Process

Tatsuhiko Nakajima (Toyota Motor)

Evaluation of vehicle dynamic performance on snowy roads is essential but time-consuming. This study integrates a driving simulator with vehicle and control models to build an MBD (model-based development) evaluation environment. By coupling and visualizing physical quantities in real time, it enables the identification of issues and consideration of countermeasures before conducting full vehicle tests. As a result, we confirmed a reduction in evaluation time and improved efficiency, offering guidance for transforming the development process.

Proposal of an Integrated Vehicle Development and Production Architecture Based on Manufacturing-Induced Physical State Variables

Ichiro Tanaka･Hiroyoshi Horibe･Takayuki Fujii･Eisei Higuchi (Honda R&D)･Mitsuhiro Takayama (Former Honda R&D)

This paper proposes a vehicle development and production integrated architecture in which a CAE predicting manufacturing-induced physical state quantities accumulated across multiple body production processes serves as a core hub, enabling physically consistent coupling of body four-major-performance CAE, manufacturing robot simulations, and prediction models of CO₂ emissions during production based on common physical state variables.

Digital Twin Construction Technology through Information Circulation between CAE and Manufacturing Robots

Takayuki Fujii (Honda R&D)･Takahiro Jinnai (Honda Motor)･Kazuto Ito (Digital Process)･Seiji Tsukada (Progress Technologies)･Ichiro Tanaka (Honda R&D)

This study proposes a digital twin construction technology aimed at eliminating discrepancies between design and manufacturing through information circulation between CAE and manufacturing robots. By reflecting robot operation conditions in CAE and feeding back on-site adjustment data, prediction accuracy is improved, and its effectiveness is validated through application to actual production.

Numerical Simulation of Airbag Inflation Using a Discrete Membrane Model Toward Prediction of In-Vehicle Pressure Changes

Satoshi Nohara (Kobe University)･Shinsuke Shibata･Kazuki Hikida･Hisaki Sugaya･Atsushi Hasegawa (Honda R&D)･Makoto Tsubokura (Kobe University)

Barotrauma cases potentially associated with transient in-vehicle pressure changes have been reported in the context of airbag performance enhancements, including increased inflation speed and deployment in new locations. In this paper, we present numerical simulations of airbag inflation under specified internal pressure using a newly developed discrete membrane model, and explore the potential applicability of the proposed method to fluid–structure interaction simulations aimed at developing methods for predicting in-vehicle pressure changes.

Study on Optimization Design Methodology for Heat components of electric vehicles using an FMI-Based Integrated Vehicle Model

Ryusaku Sawada (Sawada R&D)･Makoto Koekiba (Chuozuken)

To optimize EV thermal components early in development, this study proposes a system simulation approach. Lightweight 1D thermal-fluid models based on empirical data are integrated via FMI into a Simulink environment covering the vehicle, drivetrain, and HVAC. Parametric analysis of thermal resistance and capacity demonstrated that this method rapidly identifies robust, optimal component specifications affecting energy consumption and temperature behavior under various driving conditions, without relying on high-overhead 3D CFD.