Methodology of Scale Model Experiment for xEV Fire Torture Standard Test

Shuhei Yasuda･Risa Asada･Junichi Ogawa (Mazda)･Kohei Kajitani･Satoshi Enokida･Atsushi Yuki (Daikyonishikawa)･Masayuki Okoshi (Gifu University)･Yuji Nakamura (Toyohashi University of Technology)

Fire safety tests for rechargeable electric vehicles require the use of actual vehicles or battery packs, resulting in significant time and cost. In this study, to improve the efficiency of xEV fire safety design, we investigated a small-scale model testing method for the fire exposure standard test. A scale model applying Froude number similarity was evaluated through both simulation and experiment.

Study on Ventilation Volume of EV in the Case of Transport for COVID-19 Patient (Part5)

koichi oshino (non)

Cabin ventilation is important in the case of transport for COVD-19 patients. At the previous report, it was obtained the relation between small opening window height and the ventilation volume. It is predicted that the vehicles have the satisfied ventilation volume on the outside air inducing method at the previous report. Here, I would like to submit following two methods. First one is the ventilation of the outside air inducing method, second one is that of the small opening window height method.

A Study on Implementation of Fail Safety Function and Field Data Collection Method for Vehicle Customer Safety

SUHO LEE･SEONGHO SONG･SEUNGWAN CHO･JINHO KIM (Automotive R&D Division of Hyundai Motor Group)

The purpose of this study is to protect the safety of customers when driving a vehicle by developing a function that monitors vehicle data and provides a warning in advance when an abnormal situation occurs. Data collection devices and diagnostic logic were developed for older vehicles that cannot collect data. For example, a lack of coolant in a vehicle and a vehicle accident diagnosis logic have been developed and evaluated, and this function can be applied to older vehicles to upgrade their safety functions. Then I propose logics for calculating safe driving scores and the failure of the coolant temperature control apparatus that using the data stored in the cloud. When a customer diagnoses an abnormality in the vehicle early and provides notifications and services before experiencing inconvenience, It is believed that it will contribute to accident prevention by providing a safer mobility environment and service.

Driving the Future: Accelerating Vehicle Development Speed through Cross-Industry Synergies

Bernhard Raser (AVL List, Austria)･Toru Nishizawa (AVL Japan Ltd., Japan)･Laura Kraihamer･Johannes Linderl (AVL List, Austria)

Electrification, connectivity, and sustainability are driving unprecedented time-to-market pressure for modern vehicle development. Passenger cars, commercial vehicles, and off-road applications share similar challenges, yet often develop solutions in isolation. This paper demonstrates how cross-industry learning, combined with digitalization and model-based systems engineering, can significantly accelerate development speed. Scalable simulation, virtual validation, and AI-driven optimization enable early design decisions and reduce physical testing. Examples of AVLs proven development chain demonstrate how established methods in one domain can be adapted to others, creating a continuous feedback loop of innovation. Standardized interfaces and integrated tools further support global collaboration, ensuring quality and compliance while meeting sustainability targets.

Leveraging the Safety Concept Description Language (SCDL) for Harmonized Development of SOTIF and Functional Safety

Nobuaki Tanaka (OTSL)･Akira Takada･Shuhei Yamashita･Misako Imai (DNV Business Assurance Japan)･Toyokazu Ogasawara (Ota Development Efficiency Project)･Tomoyoshi Murata (JARI)･Kiyoshi Sasaki (Astemo)･Hideaki Nishihara (AIST)

This paper proposes a design methodology that applies the SCDL, Safety Concept Description Language, and the SRVA, Safety Requirement Violation Analysis, to SOTIF, ISO 21448, development. The approach enables progressive refinement of requirements and their allocation to system elements, similar to functional safety processes. Its applicability is demonstrated through a case study involving the representation of a SOTIF architecture for an automated driving system.

A study of ADS safety assessment methodology using near-miss data on logistics trucks

Shoji Ito･Hideo Inoue･Yasuhiko Nakano･Kenichi Uehara･Aekanan Sakulraemrung (Kanagawa Institute of Technology)･Hiroshi Fukuda (BIPROGY Inc.)･Mototsugu Miura (PTV Group Japan Ltd.)

METI (The Ministry of Economy, Trade and Industry)'s Digital Lifeline Project established a safety assessment methodology utilizing simulations with generating risk scenarios from near-miss images captured by approximately 400,000 km of logistics trucks,. This paper describes a series of foundational technologies: the categorization of near-misses, the configuration methods for agent driver models and traffic flow reflecting risks, and evaluation metrics for severity and exposure.