Market and product

Compiled by Bảo Hiền

Concept Tire Achieves 43% Recycled Material Content without Compromising Performance

A passenger car concept tire has recently been introduced as part of an EU-funded research project on circularity in the electric vehicle value chain, with approximately 43% of its composition coming from recycled materials. This is a notable result because tires must combine multiple high-performance materials to simultaneously meet stringent requirements for safety, performance and durability, making the incorporation of recycled materials into tire formulations a far more complex technical challenge than in many conventional consumer products.

The concept tire combines multiple sources of recycled materials, including recycled tall oil, steel, recovered rubber from end-of-life tires, and polyester fibers made from recycled PET bottles. One notable technology used is pyrolysis, a process in which waste tires are thermally decomposed in an oxygen-free environment to extract carbon black, which accounts for approximately one-quarter to one-third of a tire's weight, and reuse it in new formulations. In addition, waste sand generated by metal foundries is incorporated into the recycling process to produce a silica alternative to virgin raw materials.

The key significance of the result is that the concept tire still achieves the highest rolling resistance rating under the EU's standardized tire labeling system, demonstrating that a high proportion of recycled materials does not necessarily have to come at the expense of operational performance, an assumption often associated with recycled materials more broadly. When renewable materials, which account for around 13%, and materials certified under the mass-balance approach, which accounts for approximately 25%, are also included, more than 80% of the total materials used come from recycled, renewable or mass-balance-certified sources. The mass-balance approach allows renewable or recycled feedstocks to be blended into a common production stream and the corresponding certified proportion to be allocated accordingly, rather than requiring complete physical separation.

The Barrier Lies Not in Technology but in the Regulatory Framework

One of the key technologies involved, recycled carbon black produced through pyrolysis, has in fact been used commercially for several years in certain specialized product lines, such as solid tires for forklifts, showing that it is not merely a laboratory technology. However, according to independent analysis from industry observers, a major current barrier is that Europe still lacks a unified legal definition of "recycled material" applicable to the tire industry, making it difficult for manufacturers to establish a clear basis for investment in industrial-scale deployment. Industry stakeholders are calling for a standardized approach to calculating and reporting recycled material content, developed through dialogue between policymakers and businesses. If incorporated into legislation, such a framework would need to be simple, transparent and easy to understand in order to encourage substantive progress rather than create additional administrative burdens.

Generative AI Shortens Technical Literature Search Time in Tire Development

Another technological approach being adopted in the industry is generative artificial intelligence using retrieval-augmented generation (RAG), a method that enables AI to search directly through an internal repository of technical documents before generating an answer, rather than relying solely on knowledge acquired during pre-training. A Japanese tire manufacturer has recently put such a system into full operation after several years of developing various AI tools, ranging from systems for predicting the physical properties of rubber compounds and tire characteristics, to systems that automatically propose new rubber compound formulations and systems that support tire mold design through simulations combined with AI.

The technical challenge addressed by this system is common across industries with long histories: the expertise required to make decisions during product development is often scattered across vast volumes of documents accumulated over decades, including regulatory documents, process manuals, technical reports and case studies. This makes it time-consuming to find information relevant to a specific situation and leaves the process heavily dependent on individual engineers' experience.

With the new system, users only need to formulate a question according to the specific objective and work context. The AI automatically plans the search, retrieves the most relevant information from the document repository, and repeatedly evaluates the results to improve the accuracy of its answer. One notable design feature is that the system always displays links to the original source documents supporting each answer, allowing users to independently verify the reliability of the information before applying it to decision-making, rather than having to place complete trust in the AI-generated output. This approach helps reduce the risk of AI producing inaccurate information that nevertheless sounds plausible, a common problem with generative AI systems that lack clear mechanisms for tracing the sources of their responses.