The Tire Modeling and its Application in Tire and Vehicle Development course at Tire Technology Expo 2025 has been well attended, as always. However, George Mavros, who led two sessions this year, observed a shift in the demographic of the learners. Compared with previous years, more engineers from tire manufacturers participated, mainly out of curiosity because they recognize the importance of the subject, whereas automotive OEM engineers – whose daily work is less directly related – have usually accounted for most attendees.
The well-received course covered general principles of tire force generation for handling, ride and durability, as well as niche topics such as terramechanics.
According to Mavros, the long-standing challenge of modeling tire-road friction remains a key area of development. At Loughborough University, where he is a professor of intelligent mobility and vehicle dynamics, one major focus is improving this capability.
“It’s fair to say that the frictional behavior of tires is still mostly based on experiments,” he told TTI. “But there are areas where fully predictive capabilities are needed. The industry is working to develop models that can calculate friction based on road conditions and tire compounds.”
Mavros’s team at Loughborough is also advancing surface characterization and exploring ways to leverage machine learning in this field. “There’s an obsession with absolute accuracy, but that doesn’t necessarily answer all the questions. Using machine learning effectively – by analyzing large amounts of data and looking at statistical properties of friction and lesser-known aspects of tires – has a lot of potential,” he explained.
Another ongoing challenge for the industry is the effective application of models. Although existing models are mature, deploying and integrating them into the workflow to produce reliable results remains difficult. Mavros defines success as finding the most affordable and efficient path to achieve the desired result – understanding the process, the contributing factors and how to apply lessons learned without unnecessary repetition.
“A key takeaway from our course is understanding what the models do and how to use them,” he said. “Tires are among the most critical components in vehicle development, yet they’re also the weakest link. It’s a chicken-and-egg situation: you need tires to design a vehicle, but you also need a vehicle to optimize tire performance. Our course explores this dynamic and helps engineers navigate it.”
Mavros advises starting with simple models, understanding their outputs and then progressing to more advanced ones. “A common mistake is demanding too much from the start without fully grasping the multiple outputs and complex data a model provides” he said.
“There’s a lot of low-hanging fruit in modeling and simulation that often gets overlooked while people try to tackle the most complex challenges first.”
He also noted that tire sustainability modeling – particularly regarding wear and particulate emissions – is gaining attention. The biggest difficulty lies in predicting what happens to the lost tire mass: “Most efforts focus on how the tire wears rather than on where the lost material goes.”
He emphasized, “The size of particulates as a function of the tire, the road and driving style – this hasn’t been explored much.”
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