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intervene earlier and more smoothly on low-grip roads. It can also prepare for unequal grip across the vehicle. Powertrain systems can limit and distribute torque before wheelspin begins, supporting traction control, launch control, gearshift torque management, all-wheel-drive clutch control and individual motor torque vectoring in electric vehicles.
CIE: How could PFC improve adaptive cruise control and autonomous emergency braking? AT: Adaptive cruise control calculates the following distance and approach speed based on a model of the vehicle’s stopping capability. A useful representation is dsafe = vtreaction
+ v²/(2μg), using the actual
coefficient of friction and appropriate reaction allowances. If the model assumes a near-dry road, the selected gap may be too short on a slippery surface. A friction-aware system can increase the gap and reduce approach speed before the driver detects a change. Autonomous emergency braking also has to decide when to act before braking begins. Because a slip-derived estimate is unavailable at that trigger point, measured PFC can help the system adjust its intervention distance to the actual surface.
CIE: What does measured grip add to automated driving? AT: An automated driving system must plan manoeuvres the tyres can physically perform. If grip is only assumed, the motion planner must remain conservative everywhere or risk requesting forces that are unavailable on a degraded surface. Live per-tyre PFC can define more realistic limits for curve speed, emergency deceleration, and lane changes. It can also help estimate the time and distance available for a safe handover to the driver.
CIE: What other functions could use the same signal? AT: The same per-wheel signal could support grip-aware regenerative braking, aquaplaning detection, steering assistance, lane-keeping, curve-speed warnings, and more realistic pre- crash estimates of achievable deceleration. At the fleet level, equipped vehicles could also contribute measured road-grip data to live maps. These applications could reuse the existing PFC signal rather than require another sensor.
CIE: How does VibroSense TMS AT: Slip-based estimation uses wheel-speed behaviour during braking or traction events and is informative near the limit rather than during normal rolling. Camera systems classify
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the road surface ahead but generally provide a surface class, not a measured friction value for each wheel. Cloud and weather fusion provides a statistical likelihood of low grip at broader spatial and time scales and depends on connectivity and fleet coverage. A raw data-in-tyre approach can directly observe the contact patch, but transmitting continuous accelerometer data increases radio bandwidth and power consumption. VibroSense TMS performs inference in the tyre and transmits only the PFC result. These other sources can provide useful context and may complement measured PFC rather than replace it.
CIE: What evidence supports the approach? AT: A chassis system supplier independently tested the system on a Xiaomi SU7 Max fitted with Pirelli P Zero PZ4 tyres. The in-tyre node supplied real-time PFC data over CAN FD to the vehicle’s ABS controller. The test required no mechanical or hydraulic changes and no retuning of the core ABS control logic. On wet basalt, a repeatable low-friction surface with PFC of approximately 0.30, braking distance from 40 km/h fell from 63.2 to 55.5 metres. The 7.7-metre improvement is approximately 12 per cent. Results will vary by surface and vehicle because the benefit depends partly on the difference between the controller’s initial assumption and the actual grip.
CIE: How was the PFC output validated before the vehicle test? AT: VibroSense TMS output was compared with locked-wheel longitudinal friction testing, which served as ground truth
reference. The system detected transitions between dry, damp, and wet asphalt, and its PFC values were consistent with measurements from an established Tier 1 reference system at a certified proving ground. The model was trained using thousands of hours of driving data across seasons, tyre types and road surfaces, covering PFC values from approximately 0.1 to 1.2. Once deployed, the system performs inference only and does not continue learning in the vehicle. This fixed behaviour supports predictable automotive operation and validation.
CIE: How does the system integrate with the tyre and TPMS architecture? AT: The sensor node is bonded to the tyre’s inner surface and operates within the existing TPMS architecture. A TPMS system-on-chip provides an I²C interface and a standard radio connection. VibroSense TMS processes the vibration signal from the accelerometer to derive PFC. Pressure and temperature remain standard TPMS outputs, while PFC is added as an additional parameter.
CIE: How does the PFC value reach vehicle controllers? AT: The node sends PFC through the standard TPMS radio link, using 433 MHz RF or Bluetooth Low Energy, to the vehicle receiver. The software TPMS function then places the value on the vehicle’s CAN FD network. ABS, stability, powertrain and ADAS controllers can access it in the same way as other vehicle signals. Data from each tyre includes its unique identifier, the PFC value and a confidence value indicating the reliability of the estimate. The confidence value allows
receiving controllers to decide how strongly to weight PFC or combine it with existing virtual sensing inputs.
CIE: Does integration require a new vehicle communication architecture? AT: No separate communication channel or fundamental change to the vehicle’s electronic architecture is required. Processing occurs in the tyre; the result uses a standard TPMS radio path, and the software TPMS function makes it available through CAN FD. This architecture introduces direct tyre road interaction data while limiting bandwidth, power demand, and changes elsewhere in the vehicle.
CIE: What calibration is required? AT: Each tyre model requires one calibration. That calibration applies across all the model’s sizes and does not depend on the vehicle type. Separating tyre-specific signal characteristics from vehicle-level implementation reduces the calibration effort across vehicle platforms.
CIE: What is the main conclusion? AT: Braking, acceleration and steering all depend on the grip available at four small contact patches, yet controllers generally do not know those limits until a tyre begins to slip. Continuous, per-tyre PFC turns grip from an assumption into a measured input. It can give braking, stability, powertrain, and driver assistance systems a stronger basis for their decisions. Independent testing demonstrated a meaningful reduction in braking distance and showed the practical value of knowing available grip before the vehicle needs to use it.
https://polyn.ai/ Components in Electronics October 2026 23
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