Tire wear is one of the largest sources of traffic-related particulate matter and microplastic emissions. In the Fraunhofer TERIS project, four Fraunhofer institutes are developing a technology platform that will enable realistic tire wear to be generated, analyzed, and evaluated under standardized laboratory conditions. The goal is to accelerate the development of environmentally compatible tire materials and reliably predict emissions at early stages of product development.

With the successful completion of the first project milestone, the project has delivered initial results in AI-supported surface analysis, test bench concepts, and particle characterization methods, among other areas. Fraunhofer IGD is developing an intelligent optical sensing system that automatically detects and classifies tire wear surface structures using artificial intelligence. The resulting image data provide a key foundation for objectively comparing different rubber compounds and, in the future, generating reliable emission forecasts.

During the next project phase, the developed methods will be transferred to real rubber samples and integrated into the joint technology platform. In doing so, Fraunhofer IGD is making a significant contribution to a standardized, data-driven assessment of tire wear.