*This content was translated by AI.
Michelin has unveiled its 'Universal Tire Digital Twin' technology, which analyzes in-vehicle data in real time to provide recommendations for both the vehicle and the driver. This advanced software solution combines sophisticated mathematical modeling, artificial intelligence (AI), and data science algorithms to predict vehicle driving dynamics and enhance performance without requiring the attachment of additional physical sensors.
Michelin's technology can function as an embedded system optimized for the software-defined vehicle (SDV) architecture, which is central to future mobility. According to Michelin, the technology implements a virtual model by comparing real-time data on tire air pressure, wear, load, grip, and driving conditions with in-vehicle data, directly interacting with internal vehicle systems to optimize system performance. Specifically, it supports the prediction of maximum tire grip and anti-hydroplaning functions, while improving the efficiency of advanced driver assistance systems (ADAS) such as ABS.
Most importantly, by reflecting tire status data into braking algorithms in real time, the technology enhances driving stability and can reduce braking distances by several meters. It also performs tire air pressure monitoring and vehicle overload detection. Additionally, it supports preventive maintenance based on accumulated data, helping to extend tire life and maintain optimal conditions. In recent collaborative research with Brembo, the company incorporated the digital twin technology into braking algorithms to improve ABS performance, demonstrating an effect of reducing braking distances by up to 4 meters in actual emergency braking situations.
According to global market research firm MarketsandMarkets, the software-defined vehicle (SDV) market is projected to grow significantly from $213.5 billion in 2024 to approximately 1.24 trillion won by 2030. Through this digital twin technology, Michelin plans to transform tires into a core information source within the vehicle data ecosystem, positioning itself as a partner for original equipment manufacturers (OEMs) navigating the SDV transition.
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*This content was translated by AI.
