Wet ground tire modeling
Why the industry needed a new approach and what MICHELIN SIMIX built
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Stop guessing on tire trade-offs. Start simulating them.
Tire width, rim configuration, manufacturer choice; these decisions shape your motorcycle's handling. And they're made early, often without enough data. Skip the guesswork. MICHELIN SIMIX gives 2-wheel development teams battle-tested datasets to explore those trade-offs in simulation, before the prototype exists.
Still making tire calls without simulation data?
Tire decisions in 2-wheel development happen early. They're hard to reverse. And the interactions between dimensions, rim width, and vehicle geometry are subtle enough that even experienced engineers get surprised on track.
The wrong tire choice only reveals itself in testing
Width, profile, manufacturer: you have instincts. But instincts aren't analysis. Without reliable simulation data, the real comparison happens on track. Late, expensive, one option at a time.
Dimension changes with consequences nobody modeled
Mount a tire on a wider rim and the profile changes. That shifts ride height, rake, and trail, differently upright vs. leaned. These interactions are counterintuitive. Good simulation data surfaces them. Guesswork doesn't.
Test days spent on questions simulation should answer
Every session spent comparing tire options is a session not spent developing your motorcycle. Your track time is too valuable for decisions that the right datasets could settle at the desk.
Get the tire right. Build the rest on solid ground.
MICHELIN SIMIX is built on one principle: every component matters. Your tire dataset must be accurate on its own, before it touches the vehicle model. That's what makes the difference when you're exploring trade-offs, not just validating a choice you've already made.
You compare options before committing, thanks to ready-to-use datasets
Wider or narrower? Different manufacturer? Larger rim? Run the simulation, read the trade-offs, make the call. No prototype required.
You surface counterintuitive effects before they surprise you, thanks to component-level accuracy
The geometry shifts, the profile changes, the handling interactions; MICHELIN SIMIX datasets capture what standard approximations miss. Your vehicle model works with real tire physics, not compensated assumptions.
You make design decisions earlier, thanks to Michelin-calibrated data
Built from physical measurements, simulation, and real-track correlation. Battle-tested Michelin tire expertise. Not lab bench output. Not homemade approximations.
You stay agile across the project, thanks to a flexible offer
Buy, lease, or subscribe: your project, your choice. Compatible with your existing simulation tools.
Simulation datasets available for 2-wheel vehicles
Access a library of datasets built for the specific dynamics of motorcycle and 2-wheel vehicles. From early design exploration to pre-production validation.
- Handling models (Pacejka MF 5 & 6)
- NVH models (FTire, CD-Tire)
- Static stiffness characteristics
- 3D geometry files
- Standard component specifications
Built for the people who make the decisions
R&D and chassis simulation engineers
Stop crafting tire data from scratch. Get datasets that plug in immediately, accurate at component level, documented so you can stand by them when it counts.
Vehicle program managers and project directors
Tire decisions made late are expensive to reverse. MICHELIN SIMIX gives your team the data to make those calls early: with confidence, without extra test days.
Questions 2-wheel development teams ask before they start
Why is tire simulation for 2-wheel vehicles more challenging than for cars?
Motorcycle tires operate at large camber angles and generate forces that interact very differently from four-wheeled vehicles. The lateral and camber force coupling, combined with the inherently unstable dynamics of a leaning vehicle, requires specific model formulations that standard automotive datasets don't cover. Getting this right matters, because a model that works fine for a car will give you systematically wrong predictions on a motorcycle.
Why does tire and rim configuration matter so much in 2-wheel simulation?
Mounting a tire on a rim wider or narrower than its reference changes the tire's cross-sectional profile. That shifts ride height, rake, and trail, with different effects when the bike is upright versus leaned. These interactions are counterintuitive and compound across the vehicle geometry. A dataset that doesn't accurately capture the tire's baseline profile will propagate errors into every handling prediction built on top of it.
What types of simulation datasets are available for 2-wheel vehicles?
Tire datasets covering handling models (Pacejka MF 5.2 and 6.2, with appropriate camber angle coverage), NVH models (FTire, CD-Tire), static stiffness characteristics, and 3D geometry files. All are compatible with CarMaker, Adams, VI-CRT, and other major vehicle dynamics tools.
Can MICHELIN SIMIX datasets be used to compare tire options across manufacturers or dimensions?
Yes. Because datasets are ready-to-use and plug-and-play compatible with your toolchain, your team can run side-by-side comparisons: different manufacturers, different widths, different rim configurations, directly in simulation. No additional physical testing required to evaluate each option.
Do I need to run physical tests before integrating MICHELIN SIMIX datasets?
No. MICHELIN SIMIX datasets are built from a hybrid approach combining physical measurements and virtual simulation, corrected for real-world conditions. They are documented and ready to integrate into your tools from day one.
What is the right purchasing model for 2-wheel vehicle development?
It depends on your project phase. For early design exploration, where you're evaluating tire and configuration options, a subscription or lease gives you the flexibility to access multiple references without committing. For later development phases where data needs to be locked across teams, a lifetime purchase is typically recommended.
Ready to skip the guesswork?
Stop making tire calls without the data to back them. Access battle-tested, ready-to-use datasets for 2-wheel vehicles and make design decisions earlier, with confidence.
