At the beginning of 2025, the Transportation Renewable and New-energy Systems (TRANS) Laboratory from the School of Future Technology, South China University of Technology, was successfully awarded a technical development collaboration project commissioned by the GAC Research Institute. The project is led by Professor Ou Shiqi, head of the TRANS Laboratory, and will involve a one-year joint research initiative. Leveraging the laboratory’s research strengths in applying artificial intelligence to the automotive industry, the project aims to develop deep learning-based anomaly detection algorithms and modules for key passenger vehicle components, focusing on user driving condition datasets and reliability and durability scenarios.
- Collaboration Background
As a leading domestic automobile manufacturer, the GAC Research Institute possesses a vast amount of passenger vehicle powertrain data. Meanwhile, the TRANS Laboratory has established strong technical expertise in big data analytics, large-scale data processing, and deep learning, with the capability to efficiently extract valuable information from massive datasets for precise anomaly diagnosis and model development. The complementary strengths of both parties in resources and technologies will effectively facilitate the smooth implementation of the project and promote technological innovation and breakthroughs.。
- Introduction to GAC Research Institute
Established in 2006, the GAC Research Institute serves as the technical management body and core R&D hub of GAC Group. It is primarily responsible for the product development and new technology planning and implementation of GAC’s self-owned brands, including GAC Trumpchi and GAC Aion. The Institute has established a global R&D network with the GAC Research Institute at its core, supported by the GAC R&D Center in the United States, the GAC R&D Center in Europe, and the GAC Advanced Design Studio in Shanghai.
- Future Outlook
Through this collaboration, both parties are expected to achieve significant breakthroughs in the fields of automotive powertrain data analysis and intelligent diagnostics, thereby promoting the advancement of intelligent vehicle technologies. Looking ahead, as the technologies continue to be refined, the project outcomes are anticipated to be applied to a broader range of vehicle models, facilitating wider adoption of artificial intelligence in the automotive industry.
