Industry tooling up on virtual tire testing

HILTON HEAD, S.C.—It's clear that tire modeling and simulation have helped tire manufacturers reduce the time and costs associated with tire development.

But it's equally clear that there is room to improve virtual tire development, especially as tire makers look to collaborate more with partners, such as auto makers, who are looking to improve their vehicle development as well.

However, with as much progress as there has been with tire modeling, it's still not quite to the point where physical testing can be eliminated, Tom Ebbott, a Goodyear R&D fellow specializing in modeling and simulation, said during a presentation at the Clemson University Tire Industry Conference in Hilton Head.

Traditional tire development starts with analysis, often with an OEM, to set targets and expectations for tires to be made for upcoming new vehicles. That is followed by some finite element analysis or other modeling, which helps to set the concepts and the stage for building the testing cycle, he said.

It's during this cycle where you look at prototype tires and shifting those to the OEM, who may have prototype vehicles known as mules. "The mule is somewhere between the donkey that you have and the horse that you want," Ebbott said.

This process is extremely expensive, so OEMs are driving the process to be more virtual. About five years ago, an automotive engineering firm said about 65 percent of the work to develop a new vehicle was in testing and 35 percent was in modeling and simulation. By 2022, the firm predicted that it would be an 80-20 split in favor of modeling.

Ebbott said while there has been significant progress, it's not quite up to these levels.

"There is certainly much more modeling and simulation for a given vehicle program now compared to five years ago," he told Rubber News. "At Goodyear, much of the advancement has been fueled by our partnership with Sandia National Laboratories and the modeling capabilities we have developed together."

Many automotive OEMS are requiring expanded virtual collaborative development before any physical prototypes are made, and that includes virtual tire prototypes to be evaluated on the virtual vehicle.

"I think this is tough to make a direct estimate because the playing field is also changing," Ebbott said. "There are many more types of vehicles today—hybrid and electric vehicles, for example—and even on a single vehicle platform there may be many more choices of tires that all need to undergo at least validation and track testing."

For the percentage of simulation to go higher, he said, will require:

• more accurate models and predictions;
• methods to evaluate subjective performance without physical prototypes, by using technology such as the driving simulators that Goodyear recently commissioned; and
• a collaborative, upfront environment among vehicle manufacturers and suppliers where models and information can be exchanged freely.

"We want to have more upfront analysis," he said in his Clemson presentation. "It becomes more of an investigation, especially if it's an OE tire going with an OE program. You want to have more collaboration with your partner in terms of what sort of concepts they really want to look at and what they really want to have on the vehicle."

Elements for that virtual collaborative approach include predictive technologies for critical tire performances, as well as for all critical tire/vehicle performances.

That this virtual product development requires accuracy presents a major challenge.

"We need to have absolute predictions," Ebbott said. "If the tire companies are going to give the vehicle manufacturers a tire model that they are going to integrate into their vehicle, it better be pretty good. It can't just be that one is better than the other."

It's also a goal to use modeling to predict objective tire characteristics and performances, because predicting how a driver will rate a given set of tires on a particular vehicle with certain settings and on a given track has proven difficult.

"The investment that Goodyear has made into driving simulators will enable this evaluation without building physical tires and vehicle prototypes," he told Rubber News. "With this capability, the goal is to develop an all-virtual path to the right tire/vehicle combination that will meet performance targets the first time physical prototypes are built."

And just when is it time to build an actual physical tire to be tested?

Ebbott said when the program is with an automotive OEM, the timing for a physical tire submission often is dictated by the OEM's schedule.

"If this is not the case, then we use modeling and simulation tools together with data-driven approaches to take initial concepts to more-or-less finalized designs," the Goodyear R&D fellow said. "When further use of modeling tools provides diminishing returns, it is time to build prototypes for confirmation and learning."

One way to make more accurate predictions with modeling and simulation is by improving the physics for such elements as materials, geometry and loading conditions.

Out of these three variables, the most difficult to predict is materials.

Tire geometry mostly is defined by the mold shape, tread pattern and the shapes of the internal components, Ebbott said. The tire's operating environment and loading also can be defined through expected maneuvers, routes, on-board data acquisition systems and vehicle models.

But materials, and especially rubber compounds, have proven to be the most challenging aspect of modeling tire response.

"Their stress-strain response is much more complicated than say that of a metal or hard composite," he said. "Tire compounds exhibit viscoelastic frequency and temperature dependence, strain dependence, history dependence and highly nonlinear behavior. Characterizing this in the laboratory and developing a mathematical description that will carry the laboratory observations into a tire model to predict response on a vehicle is difficult."

Machine learning and combining data with physics also is useful in making more accurate models.

And time is of the essence.

"You need a tire model that will respond quickly because you can't run a bunch of simulations that will run overnight to tell me what will happen if I turn the steering wheel," Ebbott said. "It has to happen in real time."

Goodyear uses CD Tire3d/RT technology, which is similar to other offerings on the market. It can be geared toward the ride and handling portions of tire response, and has enough freedom in the full model to give good predictions on force and motion, he said.

"Historically, the way these models have been produced is by training them with testing," he said. "Of course, if you're looking at a prototype you haven't built yet, you need another way of evaluating that. If I have to build and test a prototype tire, that kind of reduces the utility of having all of this modeling put together."

Looking forward, Ebbott said future tire development likely will look different than it does now, he said. It may involve virtual collaboration that includes upfront engineering and target-setting, followed by one or two virtual tire submissions. That would be followed by one physical submission for track evaluation to make sure targets are met, and then ultimately a physical test tire for final tuning.

And all this should lead to even shorter times to market, as a smaller number of physical test tires will need to be built.

"It is difficult to quantify the cost, but on the timing, what took us three years to develop a decade ago we can now accomplish in 18 months," he said.

"And that figure should continue to decrease, although as our capabilities improve, the questions also continue to get more difficult as the market and demands continue to become more complex."